Study of the influence of the Tebessa region wastewaters on the hydrochemical quality of the alluvial aquifer groundwater’s Tebessa-Ain Chabro (N-E Algeria)

Revista Brasileira de Recursos Hídricos Brazilian Journal of Water Resources Versão On-line ISSN 2318-0331 RBRH, Porto Alegre, v. 29, e24, 2024 Scientific/Technical Article https://doi.org/10.1590/2318-0331.292420230134 1/22 This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Study of the influence of the Tebessa region wastewaters on the hydrochemical quality of the alluvial aquifer groundwater’s Tebessa-Ain Chabro (N-E Algeria) Estudo da influência das águas residuais da região de Tebessa na qualidade hidroquímica das águas subterrâneas do aquífero aluvial de Tebessa-Ain Chabro (Nordeste da Argélia) Messaoud Abidi Saad1 , Karima Seghir1 , Abdeldjebar Touahri2 , Mehdi Bendekkoum1 , Abdelaziz Bellaoueur2  & Antonio Pulido-Bosch3  1Echahid Cheikh Larbi Tébessi University, Tébessa, Algeria 2Kasdi Merbah Ouargla University, Ouargla, Algeria 3University of Granada, Granada, Spain E-mails: [email protected] (MAS), [email protected] (KS), [email protected] (AT), mehdi. [email protected] (MB), [email protected] (AB), [email protected] (APB) Received: November 20, 2023 - Revised: April 22, 2024 - Accepted: May 09, 2024 ABSTRACT Along the Algerian-Tunisian border in northeastern Algeria, groundwater is regarded as the primary source of agricultural and drinking water for the local community. This situation is the result of low rainfall and limited surface water. Finding out how wastewater discharges affect the physicochemical and bacteriological quality of alluvial groundwater is the objective of this research paper. Thirty-six wells and boreholes were targeted to collect water samples. The analysis results show that the waters ranged from acidic to neutral (6.46 ≤ pH ≤ 8.3), and moderately to highly mineralized (754 μS/cm < C.E < 11680 μS/cm). The main water types, according to the Piper diagram, are calcic bicarbonate (HCO3 - Ca2+) and calcic chloride (ClCa2+). Total coliforms and Escherichia Coli were detected in 60 and 100% of the water samples analyzed, respectively. The geospatial data shows that the chemical and bacteriological pollution progresses from upstream to downstream, from Oued El Kebir river in the South East to Oued Chabro River in the North West. The multivariable statistical analysis (Principal Component Analysis and Closer Analysis) highlighted that water mineralization is controlled by three major phenomena, which are water-rock hydrolysis interaction, leaching of geological formations, and influence of anthropogenic activities. Keywords: Algeria; Groundwater; Pollution; Wastewater; Bacteriological; Statistical analysis. RESUMO Ao longo da fronteira entre a Argélia e a Tunísia, no nordeste do país, as águas subterrâneas são consideradas a principal fonte de água potável e agrícola para a comunidade local. Essa situação é resultado da baixa pluviosidade e da limitação das águas superficiais. O objetivo deste trabalho de pesquisa é descobrir como as descargas de águas residuais afetam a qualidade físico-química e bacteriológica das águas subterrâneas aluviais. Trinta e seis poços e boreholes foram utilizados para coletar amostras de água. Os resultados da análise mostram que as águas variaram de ácidas a neutras (6,46 ≤ pH ≤ 8,3) e de moderadamente a altamente mineralizadas (754 μS/cm < C.E < 11680 μS/cm). Os principais tipos de água, de acordo com o diagrama de Piper, são bicarbonato cálcico (HCO3 - Ca2+) e cloreto cálcico (ClCa2+). Coliformes totais e Escherichia Coli foram detectados em 60 e 100% das amostras de água analisadas, respectivamente. Os dados geoespaciais mostram que a poluição química e bacteriológica progride de montante para jusante, do rio Oued El Kebir, no sudeste, até o rio Oued Chabro, no noroeste. A análise estatística multivariável (análise de componentes principais e análise de aproximação) destacou que a mineralização da água é controlada por três fenômenos principais, que são a interação hidrólise da águarocha, a lixiviação de formações geológicas e a influência de atividades antropogênicas. Palavras-chave: Algéria; Águas subterrâneas; Poluição; Águas residuais; Bacteriológicas; Análise estatística. a RBRH, Porto Alegre, v. 29, e24, 2024 2/22 Study of the influence of the Tebessa region wastewaters on the hydrochemical quality of the alluvial aquifer groundwater’s Tebessa-Ain Chabro (N-E Algeria) INTRODUCTION Algeria is rapidly becoming a more urbanized country; between 2000 and 2020, the country’s population increased from 31.1 to 44.3 million, and its annual trash output in landfills ranged from 10.9 to 13.6 million tons. As a result, the need for landfills in the country’s major cities increased (Brahmi et al., 2021). The city of Tebessa shows rapid urbanization and industrial development, resulting in a very high-water demand for human consumption or industry. This development is accompanied by an increase in the flow of discharged wastewater and the degree of pollution of surface water and groundwater, with large quantities of wastewater untreated (urban and industrial). In arid and semi-arid regions, the shallow depth of groundwater, combined with the influence of climatic conditions, significantly exacerbates its susceptibility to pollution. In 2020, the population estimate was 794528 population (Toumi & Alkama, 2022), there will unavoidably be a significant rise in the demand for water due to this population growth (Naimi-Ait-Aoudia & Berezowska-Azzag, 2014), a single sewage treatment plant - STP - located in Ain Chabro but does in it’s full operation due to the lack of wastewater transport pipes. This wastewater is discharged directly into the El Kebir and Chabro rivers, that posing a perpetual threat of water resource degradation. The Tebessa region experiences a typical semi-arid continental climate, with cold winters and hot summers and an average annual temperature of 16 °C. The region receives approximately 370 mm of precipitation on average per year (Fehdi et al., 2016), of which 332.5 mm is estimated to be actual evapotranspiration, accounting for about 90% of the precipitation. Several factors that affect the chemical composition of the aquifer, such as lithology, temperature, pH, and the amount of water available in the aquifer, as well as climatic conditions, all contribute to the degradation of groundwater quality (L et al., 2015). In addition to those natural factors, anthropogenic activities have the primary role in the degradation of the groundwater characteristics. The situation has gotten worse due to the usage of pesticides and fertilizers in agricultural activities as well as the disposal of agricultural, animal, and human waste. (Annapoorna & Janardhana, 2015; Brahmi et al., 2021; Chakraborty et al., 2022; Modibo Sidibé et al., 2019). Groundwater supplies in the studied area are declining both qualitatively and quantitatively due to anthropogenic restrictions (drawing much more than the present recharge) and environmental limitations (typically an arid climate and rainfall volatility) (Fehdi et al., 2016; Rouabhia et al., 2009; Seghir, 2014). The Wadis of El Kebir and Chabro, which have an erratic flow regime due to the extended dry season, effectively drain this area of the Merja plane. The salinity of the water varies considerably; in certain places (the eastern portion of the research area), it surpasses 5 g/L. Several studies have been conducted regarding the alluvial aquifer of Tebessa (Drias & Toubal, 2015; Fehdi et al., 2016; Rouabhia et al., 2009; Seghir, 2014). However, the incorporation of pollutant parameters indicators sets this study different (NO3 -, NO2 -, NO2-N, P, PO4, P2O5, NH4, NH3, NH3N, COD, BOD5, dissolved O2(O2-d), Turbidity (TUR)) and microbiological parameters, namely the input parameter of fecal coliforms, as their existence serves as a significant marker of the influence of human activities on the physicochemical groundwater parameters. The current research seeks to achieve several objectives: 1. Investigate the influences of natural phenomena and human activities on groundwater quality, and determine the sources of groundwater mineralization utilizing multivariate statistical methods and GIS analysis; 2. Assess the magnitude of wastewater influence on the alluvial groundwater within the study area; 3. Determine the physicochemical properties of groundwater to evaluate its suitability for drinking purposes. MATERIALS AND METHODS Study area The region of study is situated in the Merdja plain, which is located at the eastern extremity of Algeria. The following Lambert defines the plain coordinates x = 980,000/1,005,000 E and y = 245,000-258,000 N (Figure 1). The Merdja plan is a vast area that stretches in a northwestsoutheast direction. It is characterized by a relatively flat topography and is surrounded by several mountain ranges. The highlands in the region consist of mountains that reach their highest point at an elevation of 1,470 m. The altitude within the plain ranges from 750 m to 900 m. The Dyr mountain marks the northern boundary of the Merdja plain, while in the south, it is bordered by the Bouroumane, Doukkane, and Ozmour mountains. The Matlougue mountain defines the western boundary, and the Djebissa mountain forms the eastern boundary. The Merdja plain itself corresponds to a slump ditch that is filled with continental Plio-Quaternary formations (Fehdi et al., 2016). These formations are supported by the underlying DanoMontian Marl formation. Hydrographic network The digital elevation model (DEM) was used for watershed delineation, extraction of stream networks, and characterization of watershed topography (elevation map, slope map, and aspect map) by using watershed tools in GIS software (Ni et al., 2010). The Shuttle Radar Topographic Mission (SRTM) DEM data that having a resolution of 30m for the study area was downloaded from (EarthExplorer, 2023) Web site. There are three different relief zones in the study area: the plain, hill and mountain. Using the ArcGIS kernel density function to generate drainage density map, which represents the length of rivers per unit area. The maximum a drainage density value of 1.11 km/km2 was observed in the Bekkaria zone, along the Wadi El Kebir River, in the Tebessa plain, and in the extreme northeastern part of the study area at the Wadi Chabro exitory. Greater concentrations of streams and rivers are found in locations with high drainage density values, which also suggest relatively high hydrographic network densities. (Moussi & Rebai, 2021). In the study area, all surface runoff waters from the plain’s northern, southern, and eastern regions are collected by the Wadi El Kebir and Chabro Rivers, which then drain the water into the Wadi RBRH, Porto Alegre, v. 29, e24, 2024 Abidi Saad et al. 3/22 Ksob River. It is worth noting that the majority of the streams have temporary flow, depending on factors such as rainfall and seasonality. Geological and hydrogeological frameworks The Tebessa’s plio-quaternary tectonic depression (Figure 3) separates the northern Dyr highlands from the southern Doukkane and Mestrie highlands. The Mio-Plio-Quaternary detrital sediments gradually fill this depression (Figure 4) (Fehdi et al., 2016). This depression has passed through four stages: the first in Lower Villafranchien (Upper Pliocene), the second in Upper Villafranchien (Lower Pleistocene), the third at the end of Middle Pleistocene, and the fourth one at the end of Upper Pleistocene. (Kowalski et al., 2002). The majority of the research region was made up of cretaceous limestone deposits, which created an organization of anticlines and synclines. Recent alluvial deposits, gravels, conglomerates, sandstones, and other materials are described as the plio-quaternary and quaternary formations in the central region. The stratigraphic column analysis identified three aquifer formations. The shallow aquifer under study is bounded to the east and west by two large faults that are oriented NW-SE, and it covers the majority of the Tebessa tectonic depression covered by the plio-quaternary formation. The Mio-Pliocene alluvium is composed of gravels encased in an argillaceous matrix that surpasses 350 m in specific locations (Seghir, 2014). For the main sources of recharge, the aquifer primarily receives water from deeper aquifer specifically the Cretaceous formation, through faults.(Drias et al., 2022; Rouabhia et al., 2009); The aquifer’s general recharge is influenced by rainfall and other minor sources, such as surface water bodies or localised groundwater flow from adjacent places. Additionally, human activities, such as irrigation or groundwater pumping, can also influence the recharge dynamics of the aquifer. METHODOOGY The monitoring of physico-chemical and bacteriological parameters, multivariate statistical techniques like principal component analysis (PCA) and cluster analysis (CA), and the establishment of a spatial variation of the physico-chemical parameters using GIS-based data are the methodologies used in the current study. Water sampling collection 36 Samples were collected in Feb 2022 in a one-litre polyethylene bottle. The bottles are well rinsed 2-3 times by the sampled water before filling; a sampler from the Tebessa University laboratory was used for collecting samples from the observation wells or when the irrigation pump wasn’t operating. The piezometric level was measured only in the static case, The samples were collected directly from the well after 10 min of pumping the well. The samples were stored in a field refrigerator to preserve their natural conditions until they could be sent to the laboratory for analysis. The field refrigerator was used to prevent biological and chemical degradation. (Saha et al., 2019). The samples were filtered using a 0.45 mm cellulose acetate filter. The geographical coordinates of the wells, boreholes, and discharge points were obtained with the help of a handfield GPS device (Garmin). The samples were submitted to physicochemical analyses according to the protocols described by (Rodier et al., 2009) (Table 1). In December 2022, 10 samples were taken from the irrigation wells located near the discharge points and dumping sites (Table 2) for the pollution characterization elements and bacteriological analysis and covering the whole of the study area from the SW to the NE axis following the path of Wadi El Kebir River (P9, P7, P10, P11, P12, P20, P22, P23, P26, and P29 at the extreme NE) (Table 3 and Table 4). A map of the sampling Figure 1. Geographical location of the study area, localization of wastewater discharge points and water samples. RBRH, Porto Alegre, v. 29, e24, 2024 4/22 Study of the influence of the Tebessa region wastewaters on the hydrochemical quality of the alluvial aquifer groundwater’s Tebessa-Ain Chabro (N-E Algeria) Table 1. Physico-chemical analysis results (February 2022). Wells XY CE pH T HCO3 -Cl-K+Ca2+ Na+SO4 2TH Mg2+ TDS Ionic balance (m) (m) (μS/cm) °C (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) P1 1004717 250337 7910 6.93 17.5 336 1451 9.7 263.3 876.4 1179.2 584.3 321.0 5062.4 5% P2 1003245 246427 3260 7.06 18.4 414.8 375.4 9.7 151.8 372.8 469.2 191.8 40.0 2086.4 0% P3 1003247 246430 8470 6.95 17.4 262.3 1478.1 12.4 243.1 941.0 1026.4 484.1 241.0 5420.8 4% P4 1002019 244956 1094 6.91 19.1 488 75.7 3.5 77.2 44.3 59.3 144.2 67.0 700.16 0% P5 999231 245276 1205 7.33 13.5 353.8 193 4.2 92.8 80.0 89.9 143.0 50.2 771.2 -3% P6 999193 245959 3070 7.22 14.2 414.8 124.9 5.0 211.0 121.0 618.4 304.0 93.0 1964.8 1% P7 999804 246093 1094 7.51 14 463.6 87.2 6.7 30.3 72.8 28.8 111.3 81.0 700.16 4% P8 1000417 247936 1011 7.07 20.3 414.8 74.2 4.5 43.1 62.1 44.9 96.2 53.1 647.04 -3% P9 1000294 247836 1450 6.9 19.9 414.8 120 4.9 81.2 101.0 109.7 142.5 61.3 928 4% P10 994309 247614 1571 6.79 18 512.4 165 4.0 109.2 87.1 118.6 196.3 87.1 1005.44 3% P11 994773 250056 6770 7.25 16.5 463.6 1092.7 8.1 243.1 647.3 670.5 443.5 200.4 4332.8 4% P12 996073 250838 8680 7.04 16.4 439.2 1565.6 9.0 253.3 1019.3 803.5 474.6 221.3 5555.2 5% P13 995449 250973 8210 6.99 16.7 341.6 1377.6 9.2 269.0 205.0 580.6 566.0 297.0 5254.4 -9% P14 995633 252298 2760 8.3 15.9 793 337.3 8.9 27.0 426.4 213.9 142.3 115.3 1766.4 5% P15 992250 247283 2082 6.52 18.5 500.2 177.9 48.9 97.3 102.3 170.8 184.5 87.2 1332.48 3% P16 991533 247604 2165 6.7 17.5 451.4 224.5 14.6 102.7 116.4 179.8 202.1 99.4 1385.6 3% P17 991533 247604 1378 7.5 17.5 414.8 94 3.6 58.5 68.6 31.0 120.9 62.4 881.92 5% P18 991515 248973 2165 6.7 19 414.8 219.6 17.4 112.2 122.1 276.8 220.9 108.7 1385.6 4% P19 990223 251487 1668 7 18.7 530.7 438.5 1.7 160.9 137.1 242.7 305.8 144.9 1067.52 0% P20 991800 253281 933 7.17 17.5 414.8 77.2 3.7 60.1 63.6 53.9 111.7 51.6 597.12 0% P21 990641 253562 1071 6.78 14.7 384.3 77 3.2 55.8 63.6 43.1 106.7 50.9 685.44 2% P22 990060 252925 1789 7.08 17.5 390.4 258.3 3.6 68.6 132.1 59.3 144.5 75.9 1144.96 2% P23 983611 251234 4160 6.46 17.8 381.25 670.8 7.2 213.4 272.8 413.4 390.8 177.4 2662.4 5% P24 983071 251428 1904 6.81 17.5 237.9 194.5 4.7 89.2 87.8 165.4 152.6 63.4 1218.56 3% P25 983873 251159 2220 6.92 19 317.2 217.5 5.8 109.8 112.0 231.9 201.1 91.3 1420.8 5% P26 986563 255000 1732 6.75 18.8 375 201.6 3.2 88.2 89.3 95.3 150.3 62.1 1108.48 -1% P27 986047 255607 1446 6.62 18.5 366 170 3.3 80.9 82.1 80.9 137.8 56.9 925.44 0% P28 985594 255548 5550 6.46 18.7 475.8 605.4 2.5 218.4 307.8 853.9 433.8 215.4 3552 -1% P29 985149 257560 5570 6.53 17.5 378.2 890.4 4.3 277.1 337.1 661.50 496.5 219.4 3564.8 2% F11 1002639 244230 809 6.78 11.5 341.6 39.8 3.4 59.6 35.3 37.70 93.6 34 518 -1% F12 981537 252466 701 6.94 18 297.07 49.6 2.6 44.4 30.7 25.20 78.1 33.7 449 -3% F10 1004657 242619 933 7.46 14.6 350 200.2 4.5 70.1 69.3 39.50 131.7 61.6 597 -2% F09 999804 246093 1439 7.16 18.4 561.2 85.9 3.2 25.4 162.1 140.20 109.3 83.9 921 3% T11 994309 247614 3100 7.43 13.2 610 63.7 6.6 91.6 230 393.70 174.7 83.1 1984 4% F2-3 980752 253825 1537 7.11 18.5 281.21 156.7 3.6 72.9 58.6 53.90 120.9 48 984 0% F13 980919 252941 754 6.96 17.6 270.23 67.8 2.8 50.1 37.1 16.20 85.2 35.1 483 3% RBRH, Porto Alegre, v. 29, e24, 2024 Abidi Saad et al. 5/22 Table 2. Lokalization of wastewater discharges. Wastewater discharge area X (m) Y (m) Symbol Bekkaria 1000450.13 247847.909 R1 Wadi Zaarour River 994193.164 249680.694 R2 Wadi Rafana River 990942.329 250274.069 R3 Elatex <upstreame> 989581.949 252719.59 R4 Elatex <downstreame> 989709.657 252328.618 R5 The University 986641.986 254664.666 R6 Ain Chabro 983040.142 252353.44 R7 Wastewater discharge points outlet 981150.426 257060.01 R8 Table 3. Pollution characterization elements analysis (December 2022). Wells NO3NO2NO2N NH4NH3NH3N PO4P P2O5 (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) (mg/l) P9 29.1 0.13 0.04 0.23 0.22 0.19 0.80 0.20 0.60 P12 58.0 0.19 0.06 6.02 5.68 4.67 0.4 0.3 0.1 P11 22.9 0.13 0.04 0.15 0.14 0.12 2.3 0.8 1.7 P22 31.5 0.17 0.05 0.1 0.09 0.07 0.4 0.1 0.3 P7 12.9 0.01 0.00 0.19 0.18 0.15 0 0 0 P10 15.5 0.10 0.03 0.18 0.17 0.14 0.6 0.2 0.4 P26 10.4 0.02 0.01 0.08 0.08 0.06 0.3 0.1 0.2 P23 16.9 0.03 0.01 0.14 0.13 0.11 0.3 0.1 0.2 P29 9.7 0.01 0.00 0.11 0.1 0.08 0.5 0.2 0.4 P20 15.1 0.02 0.01 1.79 1.68 1.37 0.8 0.3 0.6 Table 4. Microbiologic analysis results (December 2022). Wells DCO (mg/l) DBO5 (mg/l) TDS (mg/l) TUR (NTU) O2-d (mg/l) CFT (ufc/100ml) E-Coli (ufc/100ml) P9 1806.00 85.92 670.00 2.91 4.41 0 372 P12 517 98.27 8900 2.11 50170 P11 704 85.4 522 4.55 6.32 0 115 P22 1710 75.8 770 0.15 6.62 2 6 P7 1730 108.93 3504 0.68 7.06 0 160 P10 1135 72.78 671 0.1 6.32 7 155 P26 1027 107.13 870 0.14 7.35 17 9 P23 175 122.71 713 0.06 7.65 15 2 P29 1348 97.43 1109 0.84 6.03 3 28 P20 546 88.4 503 1.74 6.32 81 points was performed (Figure 1). The in-situ measurement of physicochemical parameters, including electrical conductivity (EC), pH, and temperature, using a Multimeter brand Hach HQ40d coupled to an electrode that is kept in a solution of potassium chloride (KCl) with a concentration of 3 mol/l. The device was previously calibrated by a standard solution and as per user manual calibration steps and tested in the field. The bicarbonate was measured by the titration method, with HCl serving as the standard solution. The chemical parameters were measured at the laboratory of the geology of the Sahara LGS at the University of Ouargla; these analyses are carried out according to four methods: i. The gravimetric method: for sulfate ions SO4 2is based on the principle of precipitating sulfates in the form of barium sulfate by the barium chloride as per the chemical reaction: Ba2+ + SO4 2BaSO4. ii. The flame atomic emission spectrometry method: using a Janeway flame photometer. It is a flame photometer of emission at low temperatures intended for the simultaneous determination of Sodium, Na+, Potassium K+, and Calcium Ca2+). iii. The colorimetric titration method: for the determination of the water hardness TH (Ca2+ + Mg2+) and bicarbonate (HCO3 -). iv. The potentiometric method: used for the determination of chloride ions (Cl-) using the Titrino 716 apparatus. The chloride is precipitated by silver nitrate in the presence of potassium chromate. The apparatus must be calibrated, and it is allowed to work automatically; at the end, it displays the chloride concentration on its screen. RBRH, Porto Alegre, v. 29, e24, 2024 6/22 Study of the influence of the Tebessa region wastewaters on the hydrochemical quality of the alluvial aquifer groundwater’s Tebessa-Ain Chabro (N-E Algeria) At the Fethallah laboratory in Tebessa, the pollution chemical parameters indicated measured are the NO 3 - , NO 2 - , NO 2 - N, P, PO 4 , P 2 O 5 , NH 4 , NH 3 , NH 3 N, chemical oxygen demand (COD), biochemical oxygen demand in 5 days (BOD5), dissolved O2 (O2-d) with the Multiparameter and Photometer HANNA HI 83099 COD, and the turbidity (TUR) with the Turbidity meter type HANNA C102 and the bacteriological analysis from the same samples bags and transported to the private laboratory located in the study area and using the field refrigerator in less then six hours from the collection time. Microbiological analysis method In order to know the water’s bacteriological quality, water sampling campaigns were carried out in December 2022. This allowed us to collect ten water samples from 10 wells around the wastewater dump sites. Within the framework of this study, only standard germs, indicators of fecal contamination, were examined, and the best represented are fecal coliforms such as Escherichia Coli (E-Coli) and total coliforms (TCF). Those samples are taken in sterile plastic bags of 1000 ml with an integrated closure and designated for this type of sampling, leaving air space in the bag to facilitate the suspension of microorganisms by mixing before inoculation in the appropriate culture media, the use of sterile gloves and a gas cylinder while collecting the samples as per as samples collection standards. The samples were labeled and then stored in a cooler while being transported to the laboratory and analyzed. For these analyses, the membrane filtration (MF) method was applied. For water meant for human consumption, the World Health Organisation (WHO) specifies a bacteriological standard of 0 colonies per 100 ml of filtered water. GIS analysis of physic-chemical parameters The UTM-Nord_Algerie_Ancienne projection was utilised in the GIS environment to map the spatial distribution of groundwater quality parameter values. One of the most techniques used for interpolation is the inverse distance weighting method (IDW). The value of an unmeasured location can be estimated by measuring the values surrounding the expected location. (Ajaj et al., 2018). It is essentially based on two assumptions: First, the unknown value of a point has a direct influence on the near control point rather than the far point. Second, the degree of effect of a point is proportional to the inverse of the distance between points. (Ajaj et al., 2018; Diongue et al., 2022). Multivariate statistical methods The data collected in the field and the laboratory have been analysed using descriptive and multivariate statistical methods coupled with hydrochemical, geostatistical, and graphical approaches. The statistical approach is based on descriptive statistics, principal component analysis (PCA) and cluster analysis (CA). The PCA is used to study the origin of the mineralization phenomena, the description of the links between the variables by two-dimensional statistical techniques (Mfonka et al., 2015), and identify the major sources of anthropogenic effects on the hydrochemical groundwater quality. PCA is applied to the results of physicochemical analyses on a total of 36 samples with 12 parameters (T°C, Electrical Conductivity (EC), pH, TH, TDS, HCO3 -, Ca2+, Mg2+, K+, Na+, SO4 2-, Cl-). This method was carried out by R studio (using Facto Mine R, Facto extra, and gg biplot packages) and SPSS software. The Ascending Hierarchical Classification (AHC) or Cluster Analysis (CA) was applied to better understand the hydrogeochemical processes that govern the groundwater in the study area. The two statistical multivariate methods are applied to the results of physicochemical and microbiological analyses on a total of 10 samples with 27 parameters (T°C, EC, pH, TH, TDS, HCO3 -, Ca2+, Mg2+, K+, Na+, SO4 2-, Cl-, NO3 -, NO2 -, NO2 -N, P, PO4, P2O5, NH4, NH3, NH3N, COD, DBO5, dissolved O2(O2-d), Turbidity (TUR), CFT and E-Coli). Accuracy of analytical results Testing the ion balance while accounting for the fact that water is electrically neutral in theory is part of assessing the validity of the results. Consequently, cations total chemical equivalents must be equivalent to anions (Semar et al., 2013). It is important to note that a water chemical analysis is deemed representative only when the ionic balance is 10% or lower. The following Formula 1 determines the calculation of the ionic balance (Akoteyon, 2013): [ ] [ ) [ ] [ ] ( ) 100 – ( /BI Cations Anions Cations Anions= ∗Σ Σ Σ +Σ (1) where Σ [Cations] is the sum of the cations and Σ [Anions] is the sum of the anions (meq/l), and BI is the ionic balance given as a percentage. For each of the 36 analyzed samples, the ionic balance was computed. It is observed that 80% of the sample have an ionic balance (BI) within the range of -5% to +5%, indicating acceptable quality of the analyses. Additionally, 100% of the boreholes have a BI within the range of -10% to +10%, which is considered high but still falls within an acceptable range. Somme analysis had a BI>20% where not accepted due to the use of chloride treatment (boreholes for drinking purposes). RESULTS AND DISCUSSION Piezometry The Tebessa region has been experiencing a period of drought in recent years (Rouabhia et al., 2009; Fehdi et al., 2016; Drias et al., 2022), which has led to the overexploitation of the water table in agricultural areas. As a result, the piezometric level has dropped, and there has been an increase in the mineralization rate in the alluvial groundwater aquifer. Some wells have even become nearly dry. To assess the piezometric conditions, a survey was conducted in February 2022, and the data collected from the piezometric RBRH, Porto Alegre, v. 29, e24, 2024 Abidi Saad et al. 7/22 readings were used to create a piezometric map of the aquifer during that period (Figure 5). The piezometric level in the area ranges from 890 to 760 meters. Analysis of the isopiezes curves depicted in reveals two primary flow directions. The first direction is southeast to northwest, following the course of Wadi El Kebir. The second direction is south to north, originating from El Hammamet and extending to Morsott. In the central area, the isopiezes curves exhibit a consistent spacing, indicating a uniform flow pattern. Furthermore, in the southeast region, the flow axes diverge, indicating recharge from the Djebissa mountain. The isopiezes curves become tighter, suggesting an increasing slope of the piezometric surface and a relatively strong hydraulic gradient toward the center of the plain. The recharge of groundwater in this aquifer is influenced by factors such as precipitation, infiltration of irrigation water, the presence of quartz sands and Pliocene limestone in the eastern part, and the presence of Serdies Mountain limestone in the western part (Fehdi et al., 2016; Rouabhia et al., 2009). Hydrochemistry and statistical analysis The majority of the wells on the plain are haphazardly placed based on agricultural requirements, and their average depth is only 40 meters. The physical and chemical analysis results of the well samples are shown in Table 1. The thematic maps (Figure 6) for the chemical parameters showed that the concentrations of all major ions were highest near P2, P3, and P4 (in the southeast), P11, P12, P13, and P14 (in the north of Tebessa town), and in the northwest part at the Chabro River outlet. This may be caused by similar hydrogeochemical processes. Evaporation in this area is intense, and the groundwater depth is shallow. Furthermore, the decrease in ions concentrations in the northwest part of the study area may be attributed to the impervious layer of natural clay that can slow down the entry of pollutants into the aquifer and reduce the impact of pollutants diffusion (Chu et al., 2020). Figure 7 shows a medium to excellent correlation between these major elements and EC with nitrate (Na+, SO4 2-, Cl-, K+, Ca2+ and EC, r 2 = (0.79, 0.5, 0.64, 0.56, 0.32, 0.61) respectively. This correlation reflects the combined influence of rainfall, soil characteristics, and anthropogenic activities on the mineralization and degradation processes within the alluvial aquifer. These factors can affect the concentration of major elements and the electrical conductivity of groundwater, including nitrate contamination. The nitrate map’s regional variation (Figure 8) shows that the average values in the Tebessa, Ain Chabro, and Boulhef-Dyr areas range from 9.7 to 15 mg/l. In contrast, P12 has high levels of 58 mg/l, which are over the WHO’s recommended limit of 50 mg/l for drinking water. This well is placed in the crops class, according to the study area’s land use map (Figure 2). As a result, the use of nitrate fertilizers is the cause of this high value. The Bekkaria area (well P9) has significant levels of Escherichia coli (372 CFU/100ml) according to the map of geographic variation of the bacteria (Figure 8). This is due to septic tanks, untreated wastewater discharges, animal dung leaching, and domestic animals. Although the concentration range of 2-28 CFU/100ml for this particular germ is low in the Ain Chabro and Boulhef-Dyr locations, it should be highlighted that the presence of any of these types of bacteria makes the water unfit to drink. In consequence, Escherichia coli survives only in the digestive systems of humans and warm-blooded animals. As a result, there would be a good correlation between its concentration and the faecal pollution origin. (Zerhouni et al., 2019). PIPER and DUROV diagrams Building a Piper trilinear diagram and a Durov plot can help us understand the geochemical evolution of groundwater. Grapher software version 16.2.354 was utilized in the current investigation to create these diagrams. The Piper diagram is a multidimensional plot in which the principal cations (Ca2+, Mg2+, Na+, and K+) and anions (HCO3 -, SO4 2-, and Cl-) are represented in milliequivalents percentage concentrations in two triangle fields, and then projected farther into the middle diamond field. The Durov diagram is a composite plot made up of two ternary diagrams: a binary plot showing the concentrations of total cations and total anion (meq/l); it defines the hydrochemical processes at effect as well as the types of water that may have an impact on the water genesis. (Ravikumar et al., 2015; Singh & Kumar, 2015). Data plotted on the Durov diagram (Figure 9) supported three types of hydrochemical processes in the study area. According to Lloyd & Heathcote (1985) classification, Along the dissolving or mixing line, field 5 of the Durov plot contains 60.52% of the sample plot. Weak recent recharge from precipitation or irrigation water infiltration is the cause of this development. Furthermore, a small percentage of samples (21.05%) with Cland Na+ as the predominant anion / cation highlighted a relationship between ion exchange and rock weathering and groundwater mineralization. Reverse ion exchange has been linked to groundwater, as determined by 18.43% of samples. The Piper trilinear diagram (Figure 10) shows that the majority of the samples (81.57%) belong to the Ca2+-HCO3 -, mixed Ca2+-Mg2+-Cl-, and Na+-Cl-groups (fields 1, 3 and 2), indicating the dominance of strong acidic anions over weak acidic anions and alkaline earth over alkali (i.e., Ca 2+ +Mg 2+ > Na++K+). Rainfall recharge activities from the carbonates border to the north, south, and southeast (Figure 5) are what generate the Ca2+-HCO3 - water type, which corresponds to low EC values. The groundwater in the research region may contain calcium ions due to the dissolution of CaCO3 and Ca Mg (CO3)2 precipitates during recharge. This means that ground water in the area is mainly made up of mixtures of earth alkaline metals and has temporary hardness. Most of the water samples are coming in un-polluted to slightly polluted category (Singh & Kumar, 2015). This kind of water facies represents samples comes from boreholes that used for drinking water supply. Physico-chemical statistical analysis Descriptive analyses The descriptive analyses of the physico-chemical elements (Table 5) show that the pH of the analyzed waters varied from 6.46 to 8.3, with a mean of 7 and a standard deviation of 0.36. RBRH, Porto Alegre, v. 29, e24, 2024 8/22 Study of the influence of the Tebessa region wastewaters on the hydrochemical quality of the alluvial aquifer groundwater’s Tebessa-Ain Chabro (N-E Algeria) The pH values are relatively acidic to neutral. The temperature of the waters varies between 11.5 and 20.3 °C, with an average of 17.27 °C and a standard deviation of 2.01 °C. The electrical conductivities of these waters varied from 701 to 8680 μS/cm, with an average of 2724 μS.cm/l and a standard deviation of 2425 μS/cm; 69% of the values are outside the WHO potability Figure 2. (A) Hydrographic network and drainage density; (B) Land Use in the study area (2022). Table 5. Descrptive satistics for the water quality parameters in the alluvial aquifer groundwater. Total samples Minimum Maximum Mean standard deviation Cv WHO standard CE (μS/cm) 36 701.00 8680.00 2823.92 2425.63 0.86 400-1500 pH 36 6.46 8.30 7.00 0.36 0.05 6.5-9.5 T C° 36 7.20 20.30 17.2 2.01 0.12 25 HCO-3(mg/l) 36 237.90 793.00 412.69 106.63 0.26 300 Cl- (mg/l) 36 39.80 1565.60 380.52 455.04 1.20 250 K+ (mg/l) 36 1.70 48.90 7.06 8.01 1.13 12 Ca2+ (mg/l) 36 25.40 277.10 119.52 79.10 0.66 75 Na+ (mg/l) 36 30.70 1019.30 215.95 258.68 1.20 200 SO42- (mg/l) 36 16.20 1179.20 285.53 314.07 1.10 200 TH (mg/l) 36 78.10 584.30 227.16 150.95 0.66 50 Mg2+ (mg/l) 36 33.70 321.00 107.64 76.88 0.71 30 TDS (mg/l) 36 448.64 5555.20 1790.89 1568.61 0.86 1000 RBRH, Porto Alegre, v. 29, e24, 2024 Abidi Saad et al. 9/22 standard (400-1500 μS/cm). For major cations (Ca2+, Mg2+, Na+, and K+), Na+ ions are the most predominant and vary between 30.7 and 1019.3 mg/l, with an average of 216 mg/l and a standard deviation of 258.7 mg/l. Next comes the Mg2+ ions with a variation of 33.7 to 321 mg/l, an average of 107.6 mg/l, and a standard deviation of 76.9 mg/l. Ca2+ ions occupy the third position and varied between 25.4 and 277.1 mg/l, with a mean of 119.5 mg/l and a standard deviation of 79.1 mg/l. K+ ions occupy the last position and vary from 1.7 to 48.9 mg/l, with a mean of 7.06 mg/l and a standard deviation of 8.01 mg/l. Concerning the major anions (HCO3 -, Cl-, SO4 2-), Clions predominate and varied from 39.8 to 1565.6 mg/l, with a mean of 380.52 mg/l and a standard deviation of 455 mg/l. Next comes SO4 2ions with a variation of 16.2 to 1179.2 mg/l, a mean of 285.53 mg/l and a standard deviation of 314 mg/l. HCO3 - ions occupy the third position and vary from 237.9 to 793 mg/l, with a mean of 412.7 mg/l and a standard deviation of 106.63 mg/l. Principal omponent analysis (PCA) for the physicochemical parameters Principal component analysis was performed on 36 samples and 12 parameters (pH, T°, EC, SO4 2-, K+, Na+, Ca2+, Mg2+, TH, Figure 3. Geological map of the study area. Figure 4. Hydrogeological cross-section through the Tebessa plain. Modified from Rouabhia et al. (2009) and Drias et al. (2022). (1) Permeable zone (marly-limestones, alluvial fans, silts, calcareous crust, conglomerates, and gravels); (2) Impermeable zone (clay and marl); (3) Marly bedrock; (4) Screened interval; (5) Well name. Elevations are above sea level; (6) Water flow direction. RBRH, Porto Alegre, v. 29, e24, 2024 16/22 Study of the influence of the Tebessa region wastewaters on the hydrochemical quality of the alluvial aquifer groundwater’s Tebessa-Ain Chabro (N-E Algeria) elements and the geochemical processes that lead to groundwater mineralization. This analysis was applied to 27 parameters (T°C, EC, pH, TH, TDS, HCO3 -, Ca2+, Mg2+, K+, Na+, SO4 2-, Cl-, NO3 -, NO2 -, NO2-N, P, PO4, P2O5, NH4, NH3, NH3N, COD, BOD5, Dissolved O2(O2-d), Turbidity (TUR), Total Coliforms CFT and Escherichia coli (E.- Coli). Each hydrochemical parameter’s degree of contribution to the groundwater mineralization was determined by computing the correlation matrix (Mejri et al., 2018). The bivariate correlation matrix for 27 physicochemical and microbiological elements was presented in (Table 9): - Temperature and pH are almost not correlated with any parameter; - The EC shows a moderate correlation with NO3, NH4, NH3, NH3N, Mg2+, Ca2+, excellent correlation with TDS, K+, Na+, SO4 2-, Cl- (r2 = 0.83 to 0.96). Nitrate NO3 - shows an excellent correlation with nitrite NO2 -, nitrite nitrogen NO 2 -N, ammonia NH 3 , ammonia nitrogen NH 3 - and ammonium NH 4 (r 2 = 0.81 to 0.86). This correlation is due to the ammonium ion being transformed rather quickly into nitrates and nitrites by oxidation. A strong presence of ammoniacal nitrogen is an indication of pollution by discharges of human or industrial origin (chemical industries, nitrogenous fertilizers, textile industries. A nitrite ion is an intermediate form between the ammonium ion and the nitrate ions (Observatory of the Environment in Brittany, 2023)- However, a moderate correlation (r2=0.5) between the potassium and nitrate measurements indicates their origin (chemical fertilizer dissolution). Furthermore, a substantial correlation between Cland K+ (0.74) implies that part of the chlorides originate from KCl dissolution (Houria et al., 2020). - Finally, Cland Na+ were well correlated with NH4, NH3, NH 3 -N. The primary lithogenic sources of chloride in groundwater are thought to be the weathering of halite and evaporite and the dissolving of salt deposits, and the anthropogenic sources (Tiwari & Singh, 2014). Anthropogenic sources of chloride are septic, agricultural activity, wastewater discharges, domestic and industrial waste (Fehdi et al., 2009). We observed these maximum values at the towers of the Bekkaria zone. Table 10 shows the distribution of the eigenvalues of the different principal components. A total of four factorial axes or principal components were selected: F1, F2, F3, and F4. The variance expressed by these four components is (84.9%), and it is significant enough to provide information on the different hydrogeochemical parameters of the aquifer. Thus, 42.9% of the dataset’s variability was explained by the F1 factor, whereas 19.1%, 14.1%, and 8.85% were explained by the F2, F3, and F4 factors, respectively. The variable loading values are listed in (Table 11). A value near one suggests a strong relationship between the factors and variables. These loads are further categorized as high (>0.75), moderate (between 0.75 and 0.50), and low (between 0.50 and 0.30). F1 exhibited a moderate association with K+ and a high positive relationship with EC, Cl-, Mg2+, Ca2+, Na+, SO4 -2, TH, and TDS (Figure 14). Possible sources of SO4 2include oxidation of sulfur compounds and fertilizer produced SO4 2-. However, man-made factors, such as the quality of irrigation water. Uncontrolled fertilization is likely the cause of Ca2+, Na+, and Mg2+. Moreover, the chlorides might have been brought on by the weathering of the soil and the formation of salts. Alkaline water permeated the rocks and soil, as evidenced by the modest link between F2 and NO2 and the high correlation between F2 and NO3 -, NO2N, NH4, NH3, and NH3N. These findings explain the processes by which human behavior occurs characterized by descriptors of rainfall leaching, anthropogenic pollution, and water quality indicators (Akoteyon, 2013; Alamdar et al., 2019). The F3 axis, consisting of a positive correlation with P, PO4, P2O5 and TUR, represents 14.1% of the total Figure 13. Individuals space analysis in the factorial plan F1-F2. RBRH, Porto Alegre, v. 29, e24, 2024 Abidi Saad et al. 17/22 Table 9. Correlation matrix between the different physico-chemical and pollution parameters indicators. EC pH T HCO - 3 Cl-K+Ca2+ Na+SO-2 4TH Mg+2 NO3NO2 NO2N NH4NH3 NH 3 N PO4P P2O5COD DBO5 TDS TUR O2dCFT E-Coli EC 1.00 pH -0.14 1.00 T -0.29 -0.49 1.00 HCO30.00 0.49 -0.46 1.00 Cl-1.00 -0.13 -0.29 -0.01 1.00 K+0.74 0.25 -0.60 0.29 0.74 1.00 Ca+2 0.92 -0.45 -0.16 -0.12 0.90 0.55 1.00 Na+0.96 0.06 -0.32 0.12 0.97 0.79 0.77 1.00 SO240.98 -0.23 -0.28 -0.03 0.97 0.68 0.97 0.90 1.00 TH 0.94 -0.38 -0.24 -0.08 0.92 0.62 0.99 0.80 0.98 1.00 Mg2+ 0.94 -0.28 -0.34 -0.04 0.93 0.68 0.97 0.82 0.97 0.99 1.00 NO30.56 0.20 0.06 0.11 0.59 0.54 0.27 0.73 0.44 0.30 0.33 1.00 NO20.39 0.21 0.31 0.27 0.41 0.33 0.17 0.54 0.28 0.17 0.18 0.85 1.00 NO2N 0.39 0.20 0.33 0.25 0.41 0.33 0.16 0.55 0.27 0.16 0.15 0.87 0.99 1.00 NH40.58 0.17 -0.26 0.12 0.62 0.51 0.32 0.74 0.49 0.35 0.37 0.81 0.46 0.50 1.00 NH30.58 0.17 -0.26 0.12 0.62 0.51 0.32 0.74 0.49 0.35 0.37 0.81 0.46 0.50 1.00 1.00 NH3N0.58 0.17 -0.26 0.12 0.62 0.51 0.32 0.74 0.49 0.35 0.37 0.81 0.46 0.50 1.00 1.00 1.00 PO40.36 0.22 0.00 0.29 0.31 0.27 0.35 0.34 0.37 0.32 0.28 0.05 0.31 0.32 -0.10 -0.11 -0.10 1.00 P0.55 0.24 -0.14 0.32 0.52 0.42 0.49 0.55 0.55 0.47 0.44 0.20 0.36 0.38 0.14 0.14 0.14 0.96 1.00 P2O50.27 0.21 0.03 0.25 0.22 0.19 0.29 0.23 0.30 0.26 0.22 -0.06 0.23 0.24 -0.22 -0.22 -0.22 0.99 0.92 1.00 COD -0.49 0.27 0.20 0.06 -0.50 -0.43 -0.51 -0.47 -0.48 -0.49 -0.46 -0.13 0.08 0.01 -0.42 -0.42 -0.42 -0.23 -0.37 -0.16 1.00 DBO5 0.17 -0.26 -0.40 -0.44 0.17 0.36 0.21 0.09 0.18 0.24 0.27 -0.19 -0.56 -0.54 0.05 0.05 0.05 -0.41 -0.34 -0.41 -0.38 1.00 TDS 1.00 -0.14 -0.29 0.00 1.00 0.74 0.92 0.96 0.98 0.94 0.94 0.56 0.39 0.39 0.58 0.58 0.58 0.36 0.55 0.27 -0.49 0.17 1.00 TUR 0.44 0.41 -0.15 0.26 0.41 0.49 0.31 0.50 0.43 0.30 0.29 0.35 0.40 0.42 0.22 0.22 0.22 0.84 0.85 0.80 -0.11 -0.26 0.44 1.00 O2d-0.27 -0.10 -0.19 -0.19 -0.27 -0.16 -0.16 -0.37 -0.27 -0.14 -0.12 -0.61 -0.59 -0.58 -0.47 -0.47 -0.47 -0.23 -0.27 -0.18 -0.25 0.47 -0.27 -0.57 1.00 CFT -0.28 -0.58 0.26 -0.42 -0.27 -0.37 -0.09 -0.37 -0.26 -0.15 -0.22 -0.48 -0.54 -0.47 -0.25 -0.25 -0.25 -0.30 -0.33 -0.27 -0.47 0.47 -0.28 -0.56 0.66 1.00 E-Coli -0.01 0.24 -0.01 0.46 -0.03 0.27 -0.13 0.10 -0.03 -0.12 -0.11 0.37 0.42 0.40 0.14 0.14 0.14 0.14 0.09 0.11 0.43 -0.26 -0.01 0.48 -0.75 -0.57 1.00 RBRH, Porto Alegre, v. 29, e24, 2024 18/22 Study of the influence of the Tebessa region wastewaters on the hydrochemical quality of the alluvial aquifer groundwater’s Tebessa-Ain Chabro (N-E Algeria) variance; the main sources of phosphates in water are industrial effluents, wastewater discharges (which contain synthetic detergents with phosphate bases), and land runoff from farming operations that employed inorganic fertilizers (Lewoyehu, 2021). The factorial plan F4 correlated with E-Coli and COD, this axe represente the hygienic quality of water. Cluster analyses In order to complete the interpretation of the PCA, a hierarchical ascending classification was performed. The technique used is a variance aggregation technique or Ward’s method based on the calculation of the Euclidean distances between statements. The variance aggregation techniques attempt to optimize, according Table 10. Eigen values and percentages expressed for the three main axes for total physicochemical and microbiological analyses. Component Initial eigen values Sums extracted from the charges square Total % of variance cumulative % Total % of variance cumulative % 111.576 42.876 42.876 11.576 42.876 42.876 25.154 19.087 61.963 5.154 19.087 61.963 33.804 14.088 76.051 3.804 14.088 76.051 4 2.391 8.854 84.905 2.391 8.854 84.905 5 1.547 5.728 90.634 1.547 5.728 90.634 6 0.919 3.402 94.036 7 0.769 2.849 96.885 8 0.719 2.665 99.550 9 0.122 0.450 100.000 Table 11. Correlation of total physicochemical and microbiological parameters with their factorial axes. Parameters component 1 2 3 4 EC 0.914 0.345 0.176 0.010 pH -0.368 0.225 0.294 0.243 T-0.297 0.054 0.113 0.097 HCO3-0.146 0.132 0.340 0.294 Cl-0.898 0.395 0.144 -0.006 K+0.648 0.321 0.113 0.075 Ca2+ 0.966 0.057 0.147 -0.075 Na+0.773 0.563 0.199 0.060 SO4 20.957 0.213 0.171 0.008 TH 0.981 0.067 0.113 -0.054 Mg+2 0.981 0.079 0.066 -0.025 NO30.271 0.870 0.041 0.345 NO20.099 0.666 0.357 0.487 NO2N0.077 0.717 0.381 0.417 NH40.318 0.891 -0.129 0.000 NH30.318 0.891 -0.130 0.000 NH3N 0.320 0.891 -0.129 0.003 PO40.235 -0.082 0.962 0.055 P0.383 0.100 0.902 -0.006 P2O50.183 -0.192 0.957 0.055 COD -0.416 -0.325 -0.193 0.753 DBO50.366 -0.188 -0.555 -0.455 TDS 0.914 0.345 0.176 0.010 TUR 0.289 0.149 0.745 0.323 O2-d -0.138 -0.431 -0.179 -0.732 CFT -0.158 -0.177 -0.235 -0.805 E-Coli -0.060 0.136 0.082 0.807 RBRH, Porto Alegre, v. 29, e24, 2024 Abidi Saad et al. 19/22 to criteria related to inertia calculations, the partition obtained by the aggregation of two elements (Bebba, 2017). The dendrogram (Figure 15) represents the result of the cluster analysis; we distinguish four main families of variables. The first family is grouped (T, NO3, PO4, P2O5, P, NO2, NO2N, TUR, NH3N, NH4, NH3, CFT, K+, pH and O2 _d) represented the netrogenous and phosphorus compounds, the groundwater contamination in NO 3 - and P can occur from a variety of sources, including agricultural, urban, and uncontrolled discharges, as well Figure 14. Correlation circle of physico-chemical and microbiological parameters on F1-F2 plane. Figure 15. Dendrogram of total physico-chemical and microbiological parameters for the alluvial aquifer. as from the oxidation and/or decomposition of organic waste linked to human activities (Soro et al., 2019), this family is to be related to the diversity of mineralization processes strongly dependent on the pH of water. The seconde family grouping of major ions has a high concentration (Cl-, SO4 2-, Na+, Ca2+, and TH) and the presence of E-coli and DBO5 shows that we have two sources of mineralization of these waters; the first is natural from water-rock interactions and residence time in the aquifer, and the second source is due to surface inputs by infiltration of urban RBRH, Porto Alegre, v. 29, e24, 2024 20/22 Study of the influence of the Tebessa region wastewaters on the hydrochemical quality of the alluvial aquifer groundwater’s Tebessa-Ain Chabro (N-E Algeria) pollutants generated by human activities; the third closer presented by COD. Finally, the fourth one is formed by the parameters CE, TDS, which determine the degree of the waters’s mineralization. CONCLUSION In conclusion, the study conducted on the hydrochemical quality of the alluvial groundwater of Tebessa reveals a significant influence of wastewater on its characteristics. The investigation utilized hydrochemical methods, geostatistical analysis, graphical representations, and multivariate statistical analysis to assess the hydrogeochemical and microbiological characteristics of the water. The alluvial aquifer in the region has an average depth of 21 m. The physical properties of the water indicate that the temperature ranges from 13.5 to 20.3 °C, with an average of 17.5 °C. The pH values of the water range from 6.46 to 8.3, with an average of 6.97, suggesting a neutral to alkaline nature. The electrical conductivity varies from medium to high, with values ranging from 701 to 8680 μS.cm-1 and an average of 2745 μS.cm -1 . Three primary factors were found to influence the mineralization of the water in the region by Principal Component Analysis (PCA) and Cluster Analysis (CA): contact water-rock, residence time or hydrolysis, and precipitation-soils. The hydrochemical properties of the alluvial groundwater are also deteriorating as a result of human activity, such as the generation of waste pollutants. Elevated levels of total coliforms and faecal germs (E-Coli) suggest recent human contamination (Yanko, 2000). Thematic maps of chemical parameters illustrate that the southeastern zone of the study area is more affected, potentially due to the use of wastewater in irrigation and the application of chemical and organic fertilizers in agriculture. The dominant chemical facies in the water include Ca2+-HCO3 -, mixed Ca2+-Mg-Cl-, and Ca2+-Cl-. Overall, the study highlights the strong influence of anthropogenic activities on the physicochemical and bacteriological quality of both superficial and groundwater in the study area. These findings emphasize the importance of implementing appropriate measures to mitigate the degradation of groundwater and ensure their sustainability. 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Karima Seghir: Conception and design, data acquisition, data analysis and interpretation, methodology, and final approval of the version to be published. Abdeldjebar Touahri: Conception and design, data acquisition, data analysis and interpretation, methodology, and final approval of the version to be published. Mehdi Bendekkoum: Data acquisition, data analysis and interpretation, and final approval of the version to be published. Abdelaziz Bellaoueur: Data acquisition, data analysis and interpretation, and final approval of the version to be published. Antonio Pulido-Bosch: Methodology, and final approval of the version to be published. Editor-in-Chief: Adilson Pinheiro Associated Editor: Edson Cezar Wendland