Groundwater quality delineation based on AHP method and GIS: a case study in Regueb basin, Central-Tunisia

doi:10.21203/rs.3.rs-1602041/v1

The Regueb basin constitutes an important agricultural area in Sidi Bouzid region (central Tunisia). Water scarcity and quality degradation propose an adequate management strategy. This strategy influenced by several parameters. In this context, the combining AHP approach with GIS tools was used as a method to study the water irrigation quality according to six parameters (EC, TDS, Na⁺, SO₄²⁻, Cl⁻ and SAR). The finality result was shown as a map present the lateral variation of equality index in Regueb basin. The most parameter that influent the water quality are EC and TDS, with mean concentrations of 2200 mgL^− 1 and 15400 mgL^− 1, respectively. Water quality map show a variation throws out the basin indicate that the most affected zone is located near the Sebkhat mechiguigue. The dissolving of evaporate sediments (halite and gypsum) in groundwater explains the relevance of the Na⁺, Cl⁻ and SO₄²⁻ where the quality degradation condition was conserved. This work also prove that the systematic control of wells is essential for a good evaluation resource. This study can have used as a foundation of a new management strategy help to minimise the degradation of groundwater quality in Regueb basin.

hydro-chemistry

irrigation water

Groundwater

AHP

Central-Tunisia.

All most of natural resource (water, soil…) are often used and investigated in the majority of sedimentary basin. those resource can be influenced by natural and artificial influences. (Hamed et al., 2018; Abdelkarim et al., 2022). In a dry area, groundwater resource presents the most basics water resource, specially in central Tunisia (Ncibi et al., 2020a, b). Since the importance of this later a required management strategy both in quantitative and qualitative way (Hamed et al., 2008, 2010; Ncibi et al., 2018). However, the degradation of groundwater has been the subject of numerous researches. Precisely, the major origins of salinity are many of which: (1) saline intrusion from Sebkhat, chott and Garaat to the aquifer (Hamed 2015a, b); (2) water- rock interaction (Hamed et al., 2014); (3) climate impact (Besser and Hamed 2019). This problem has been encountered in several countries such as France (Blavoux et al., 2004), Argentine (Gomez et al., 2020) and Algeria (Hamed et al., 2018). Water quality challenges are frequently present in conjunction with an existing difficult situation for water resource management. The scarcity and degradation of water quality necessity an effective management system (Ncibi et al., 2020 a). Several writers employed the Water Quality Index (WQI) to assess groundwater quality. The calculation indices should be used the parameters related to the groundwater applications (Mokarram et al., 2019). There are several water qualities indices that has been developed, such as Turkey (Water Quality Index) (Ayla et al., 2014), identify groundwater potential zones using Geographic Information System (GIS) and Fuzzy Analytical Hierarchy Process tools to achieve multi-attribute decision making across several thematic layers that affect India's groundwater resources (Singh et al., 2019; Ncibi et al., 2020 b). Water quality index is challenged by integrating measured values (each place needs a certain number of measured values) for water quality standards because it’s unaffected by the number of parameters used to compute it but it allows the weights assigned to each criterion to be modified. So the weights allocated to each criterion can be altered, it's frequently used to analyze water quality. Therefore, One of the Multi-Criteria Decision-Making (MCDM) approaches that can be used to change the weights of water quality criteria is the analytic hierarchy process (AHP). The benefit of using this strategy is that it reduces susceptibility to changes in input parameters and allows for local index application (Ayla et al., 2014). So, using of the AHP in this study is to asses the WQI of the groundwater in the Regueb basin in Tunisia's central region. This area encompasses a subsiding basin with a fault network that enables water circulation between aquifers (shallow and deep). In Tunisia, various studies have evaluated water quality by giving traditional weights to water quality parameters, but no study has employed the MCDM approach to change the weights (Ncibi et al., 2020a, b). The major goals of Regueb basin were the WQI investigation using the AHP technique in the study area and the hydro-chemical characterisation.

The research area is in the Regueb basin, Central Tunisia. It has a surface of 1050 Km² (Fig. 1). The Kairouan basin and Jebel Khechem limit it from north, Bouthadi anticline from Northern-East, Jebel Telil in Eastern, Mazzouna Range from southern and the Tunisian dorsal (Jebel Jabes, Jebel Gouleb, and Jebel Goubrar) in the West. The climate in the Regueb basin is semi-arid, with variable precipitation in the average of 250 mm year^-1. The temperature varied between 19°C winter and 45°C in summer, which influence the evapotranspiration to attender the 2300 mm year^-1 (Hamed et al., 2018; Ncibi et al., 2020a, b; CRDA, 2021).

Fig.1

Geological and tectonic setting

Regueb basin is located in the eastern boundary of Central Tunisian. It is made up of oriented folds North West-Sud West that divide syncline basins holding Tertiary deposits. The lithostratigraphic unite subdivisions reveals a stratigraphic succession spanning the Triassic to the Quaternary. The olds series are found in the North-South Axis (NOSA) in the western part of the study area and in the Mazzouna Range in the West. The extrusive evaporitic rocks from the Triassic outcrop in Jebel Goubrar and Jebel Rheouis. These Triassic rocks are composed with gypsum, halite and anhydride, which are easily dissolved and so have an impact on water mineralization (Boukadi 1994; Dlala 1995; Zouaghi 2008; Ncibi et al., 2020a, b; Hamed et al.,2021). The dolomitic massive limestone of Nara Formation represents the Jurassic series (Burollet 1956). The most of surrounding anticlinal layers are centered on the Cretaceous series, which outcrops in the study area. The Lower Cretaceous series consist from bottom with detrital deposits and with sandy and carbonate deposits in top (Zouaghi 2008). Carbonate series (dolomite, limestone, and marl) are abundantly in upper cretaceous and presence of clay sequences interspersed with evaporitic deposits occurring during Cenomanian (Creuzot et al.,1989). The central Tunisia characterized by a regular sedimentation snapping the Cretaceous to the Tertiary. Messiouta, Ain Grab, Mahmoud, Beglia and Saouaf are the Formations of Neogene, often found in slumped areas (Zouaghi et al.,2011). The Mio-Pliocene layers are fine to coarse in character and lie unconformable atop those from preceding areas. The study area contains extensive outcropping of Quaternary rocks, which is characterized by diversity of sedimentation (Hajji et al., 2018). The deposits are predominantly detrital, fluvial and aeolian in origin, and have a high permeability.

The Regueb basin permeate many faults, which controlled the geometry of hydrogeological basin and the groundwater circulation. The collapsed segment of the anticline of Bir-Ali Ben khalifa basin changes the flow direction of Leban Wadi from NNE towards Sebkhat Mecheguigue to NE-SW towards the Ouedrane basin. The synsedimentary deposits and the multiphase deformation induced by two major faults running in opposite directions: the first, the NE-SW direction, which affects the Goubrar, Gouleb, Khechem, and all of the western boundary; and the second, the NW-SE to E-W direction, which affects the Bouthadi and Bir-Ali ben Khalifa anticlines, as well as the Mezzouna chain, which resulted in intense fracturing of Cretaceous deposits, facilitating the drainage of the water in limestone and dolomitic deposits. It's a Mio-Plio-Quaternary filling aquifer with many layers. The reservoir levels are interspersed by impervious to semi-permeable layers in sandy clay formations (clay and sandy clays).

Hydrology and Hydrogeological setting

The subsidence of the Regueb basin allowed for the formation of a very deep ditch filled with continental detrital deposits in the form of alternations of sand and clay with a wide range of intermediate terrains. The Mio-Plio-Quaternary is credited with this series. Boreholes drilled to the north and south of the plain revealed the asymmetry of the Regueb basin's structure (Gassara 1980). The continental deposits were discovered near the basin's northern closure (drilling el Akerma 800 m), whereas the infill becomes weaker towards the plain's southern end. At an elevation of 417 meters, this is how the Ksar Gheris borehole reached the Eocene. There are two major components: (1) The Mio-Plio-Quaternary detrital complex, which contains numerous aquifer layers and consists of sandy to sandy-clayey foundations. In certain areas, the thickness of this entity exceeds 1,000 meters. (2) The Eocene limestone that is more than 800 m to the north and less than 450 m to the south of the plain and is not caught in the Regueb basin. Thus, only the Mio-Plio-Quaternary aquifer deposits are of hydrogeological relevance. The Regueb basin is characterized by a dense hydrographic network generated by Leben Wadi, which eventually becomes Ouadrane Wadi as it approaches the Sfax plain. The following are the groundwater movements: (1) In the north, the flow is NW-SE from Jebel Khechem and Jebel Goubrar to the Sebkhat Mechiguigue, which serves as the water table's natural exit. Total endorsees characterize the sheet at this point. The hydraulic gradient is around 1.5%, (2) The converging streamlines in the plain's center reveal a flow from NW-SE to West-East and (3) The flow SW-NE towards Leben wadi, materializing a groundwater supply through infiltration of Leben Wadi inputs (Fig. 2).

Fig.2

Methodology

Analytical techniques and data sets

During February 2021, 48 water samples were selected and collected from accessible wells. The chemical element (Mg²⁺, Na⁺, Ca²⁺, K⁺, Cl^-, NO₃^-, HCO₃^2-, and SO₄^2-) have been analyzed at the Laboratory of physical and chemical Analyses of Soil and Water of the Regional Commissariat of Agricultural Development (CRDA) of Sidi Bouzid. Titration was used to determine Mg²⁺, Cl^-, HCO₃^2-, and Ca²⁺. Using flame atomic absorption spectrophotometry, the concentrations of SO₄^2- were determined. Flame photometry was used to determine the elements K⁺ and Na⁺. NO₃^- concentrations were determined nitrate meter LAQUAtwin B-743, and SAR values were calculated using Eq.1:

Eq.1

For each sample, an ionic balance error was calculated and utilized as a framework for verifying the analytical data's quality. A duplicate analysis was used to assess the reproducibility of the analytical processes, and the duplicate results did not differ by more than 10% of the mean. Ionic balances were calculated using Eq.2:

Eq.2

Milliequivalent per liter (meq/L) is the unit of measurement for all ionic concentrations.

The Analytic Hierarchy technique (AHP)

AHP is an MCDM (Multi-Criteria Decision-Making) method for analyzing complicated decisions including multiple criteria that was created in the 1970s (Staaty 2008). The current study evaluates the irrigation water quality based on a multicriteria analysis using the AHP method. The AHP approach serves a variety of functions often contradictory, functions, including framing an issue, representing and quantifying decision criteria, and connecting these criteria to larger goals, most notably classifying water quality from each criterion (SAR, EC, TDS, Na⁺, SO₄^2- and Cl^-). As shown in fig.3, the AHP approach is a commonly utilized concept that is built on solid mathematical and psychological underpinnings (Alya 2014; Golden et al., 1989; Lui 2004).

Fig.3

For each criterion, a matrix A of pairwise comparisons is produced. The matrix A's components i and j are numerical entries that indicate the relative importance of element i over element j in comparison to the comparable element at the next higher level. Thus, the matrix A has the form of the Eq.3:

Eq.3

where n is the number of criteria defined in step one.

Criterion i is more (less) important than criterion j if the value of element (i, j) is greater (less) than 1. Element (j, i) of the matrix is the inverse of element (i, j) (Tab.1, 2). The principal elements of the matrix A are calculated in order to estimate relative priorities among the n elements of the matrix A. Then are weighted and rated in relation to the criteria or sub-criteria (Ayla 2014; Bhushan and Rai 2004).

Table 1

Table 2

The matrix's consistency is assessed in order to ensure that the priority ratio is consistent. Based on the CI and the Random Index RI, the Consistency Ratio CR is calculated using Eq.4 (Hsu and Hu 2008):

Eq.4

The consistency index (CI) is calculated using Eq.5:

Eq.5

Where max is the biggest matrix or major eigenvalue, and n is the number of elements in the matrix being compared.

The random index RI is obtained by performing various simulations as shown in Tab.3.

Table 3

The weights of the sub-criteria are multiplied by the rating of each alternative, and the results are summed to provide local ratings for each criterion. The rating of each alternative is then multiplied by the weights of the sub-criteria, and the results are aggregated to produce local ratings for each criterion (Fig.3).

The classification and mapping of water quality

Water Quality Index (WQI) was then developed using six criteria (SAR, TDS, pH, Na⁺, SO₄^2- and Cl^-) that were grouped into five classes (Tab.4). Each quality criterion was allocated to one of five classes for each water sample. Thus, various levels of groundwater suitability for irrigation uses are detected: excellent, good, permissible, doubtful and unsuitable. Each of these groups related to a specific range of quality criterion values (Tab.4).

Table 4

Based on the AHP, the calculation and the weighting of each criterion done. The evaluation of WQI was calculated using the equation Eq.6 below:

Eq.6

Where W_k and C_k are the weight and class of quality criterion k, respectively (Tab.4). Finally, a spatial distribution map of the WQI has been generated based on GIS.

Statistical analysis (ACP)

A quantitative and independent method to groundwater classification appears to necessitate multivariate statistical analysis, which allows for the reduction of a large dataset of variables into a few components and the clarification of chemical parameter correlations. Principal Component Analysis (ACP) was performed on the 48 groundwater samples using SPSS 2021 software based on 10 physicochemical variables (TDS, pH, SO₄^2-, HCO₃^-, Ca²⁺, Mg²⁺, Na⁺, K⁺, Cl^-, and NO₃^-). The data was standardized using Pearson's correlation coefficient.

Hydrochemical analysis (ACP)

The Hydrochemical analysis allowed for a comprehensive evolution. The piper diagram (Fig. 4.b) has been used to compare the ionic composition of the water samples. Groundwater samples decomposed in two groups: (i) chlorinated-sulfate-calcium, (ii) sulfate-chloride-calcium. According to the PCA, two principal components could explain 69.28% of total variance in parameters, implying that the hydro-chemical evolution of groundwater is governed by two distinct processes (Fig.4.a). The first extracted PC (F1) explains 40.29% of the total variance. This component is linked to high TDS, Cl, SO₄^2-, Na⁺, Mg²⁺, and Ca²⁺levels, as well as moderate NO^3- levels. (Fig.4.a). As a result, it almost entirely encompasses natural processes of geological rock breakdown. It generally pertains to the cations exchange process and the accelerated dissolving of evaporate minerals from Triassic strata. It also demonstrates the role of anthropogenic activities on water mineralization (high loading of nitrate for MPQ samples). The second factor (F2) accounts for 28.99% of the overall variation. It is mostly fueled by HCO₃^- (Fig.4.a) implying that carbonate dissolution has an impact on water mineralization. High mineralized waters suggest accelerated solubility of evaporate minerals and chemical weathering of fertilizers, as shown by the projection of variables and people on the factorial design (F1, F2) in Fig.4. a. It also indicates the dominance of carbonate weathering (high HCO₃^- loading), as well as low salinity levels, which indicate a short residence duration, quick water circulation, and regular replenishment.

Fig.4

Fig.5 shows descriptive data regarding physical-chemical parameters of groundwater samples. Spatial distribution map of TDS in groundwater shows a value ranging from 1,040 mg/L to 15,400 mg/L. (Fig.5.b). To the North of the study area, near evaporation areas of Sebkhat Mechiguigue, a high salinity values (more than 15,400 mg/L) were reported. Those parts characterised by the groundwater depth very low (6 meters) which lead to high evapotranspiration. As shown in the Fig.5, all the chemical elements such as Na⁺, Cl^-, Ca²⁺, and SO₄²present a lateral version throughout the study region. The most importing values of this element are located in the downstream part of the basin where the Sebkhat formation dominate the land cover, which has a much imparted impact in the contamination of the groundwater resources. In other hand, the variation of these element show the over concertation pf same element such as Na⁺, Cl in the upstream part of the Regueb region due to the over use of the chemical production the agriculture activities (Fig.5.c, d, f) Which is related to the evaporation deposits.

Fig.5

Determination and modeling of solubility for CaSO₄·2H₂O ⇔ Ca²⁺ + SO₄²⁻+ 2H₂O is causes of dissolve of minerals gypsum and/or anhydrite and/or halite. Sulfate and Calcium levels in groundwater samples were found to be closely related between them (Fig.6). Ca²⁺ concentrations show a good correlation with SO₄²⁻; it my caused by the gypsum dissolution. In other hand, the sodium and chloride present a good correlation as shown in Fig.6.c related to the dissolution of halite (NaCl) reduces the abundance of chloride and sodium in natural waters. Cl^- is a stable and conservative tracer of evaporates; it is very soluble (very rare to contributes in saline precipitation) and does not intervene in oxydo–reduction process, hence the association between the amounts of Na⁺ and Cl^- was investigated (Fig.6.c). Based on Fig. 6d, many samples in the study area showed greater sulfate than sodium contents, which may be due to halite dissolution. In addition, the excess of chlorine compared to Na⁺ explains the base rate of clay minerals which is poor. The majority of the samples include more chloride than calcium, and these two elements are well connected at low concentrations, most likely because to the dissolution of evaporates, which contrasts the Ca²⁺ concentrations in the samples with the chloride concentrations (Fig.6.b).

Fig.6

The Analytic Hierarchy Process (AHP)

The AHP was used to calculate the WQI for the groundwater samples. The TDS, EC, SO₄^2-, Cl^-, Na⁺, and SAR were among the six quality criteria used in the AHP. The criterion weights are show in Table 5. SAR (0.36) > EC (0.24) > TDS (0.15) > Cl^- (0.13) > SO₄^2- (0.08) > Na⁺ (0.05) was the order of AHP criteria weights. The consistency ratio (CR) of the AHP model (0.052) was within the suitable limit (CR < 0.1) (Tab.5).

Table 5

Groundwater samples were grouped into five classes: excellent, good, permissible, doubtful and unsuitable, which accounted for 43.75%, 22.91%, 18.75%, 8.33% and 6.25% of the samples, respectively (Fig.7). Groundwater quality starts to deteriorate in the east and N-E directions, and it deteriorates the greatest in low-elevation locations. In the N-W and S-W, the water quality looks to be acceptable for irrigation. Therefore, the quality of the water seems to deteriorate along the direction of groundwater movement.

Fig.7

According previous research (Bozdag 2015; Sutadian et al.,2017; Ncibi et al., 2020 b) MCDM methods such as the AHP are especially useful because they employ pairwise comparisons, the problem of random weight assignment associated with criterion is minimized. The AHP-based method used to assess the quality of irrigation water in the Regueb basin in this study can be applied to other places. An AHP-weighted water quality index can be used to transform multiple factors into a single relevant criterion (an index) for a given hydrogeological system, and to determine water quality levels in the system based on several criteria. This method makes adding and removing criteria simple and customizable. It can incorporate data on many water quality variables into a full index while reducing the probability of inaccuracies in the same region, this AHP-based water quality index differs from those applicate by several researches such as Sarkar et al (2021), and Mishra et al (2022). In other hand, same disadvantage of the approach utilized by Gharbi et al (2019) is that it excludes the quality indicators that contribute to the majority of the variability in irrigation water quality (Meireles et al., 2010, Ncibi et al., 2020 a). Because data regularly influences the decision maker's choices, the AHP has a distinct benefit (Saha et al., 2021). The AHP and other MCDM techniques are particularly advantageous since they use pairwise comparisons, which eliminates the problem of criterion random weight assignment. The AHP- based technique used in this study to assess the quality of irrigation water in the Sidi Bouzid region's northeastern basins is also relevant to other agricultural regions, according to previous research (Şener et al., 2022; Ncibi et al., 2020, Saha et al.,2021). The removal and/or inclusion of other criteria has no effect on this strategy.

The quality of water is assessed using AHP and GIS in the Regueb basin. It is one of the most significant agricultural areas of central Tunisia, the preservation of irrigation water quality is critical for this region. The geometry and lithology of the Regueb aquifer system are fairly diverse. It is made up of a number of intriguing reservoir levels. The thickness of the aquifer levels captured in the area is variable. The semi-deep level, on the other hand, is the most essential level because it is placed below the static level and is easily accessible. The weights of the quality criteria (EC, TDS, Cl^-, Na⁺, SO₄^2-, and SAR) that were used to evaluate the WQI were determined using the AHP method. The hydro-chemical characterisation of groundwater samples was based on the spatial distribution of chemical elements and the connection diagram between their concentrations when evaporitic minerals were dissolved. A significant EC value is assigned to some samples near sebkhat mechichigue. As a result, this sebkhat poses a salinity risk to the Regueb basin. Because of the risk of salinity, the groundwater in this research region is unsuitable for irrigation. For a given hydrogeological system, the AHP can be used to convert numerous variables into a single acceptable criterion (an index). It also reduces the chance of mistakes and ignores the quality characteristics that account for most variation in irrigation water.The WQI maps established in this study could be used as a tool for decision-making to help set recommendations in groundwater management in the Regueb basin. Effective measures should be applied to protect groundwater against deterioration in the study area. It is extremely recommended: (i) to use of treated water for groundwater recharge, in this way, we achieve two goals: preventing polluted water to infiltrate towards groundwater, and enhancing groundwater raising the piezometric level, (ii) Ameliorate the water and soil conservation strategie (dams, tabia…) in the recharge area in order to use the maximum of water provide from precepitation to use in agriculture and to ameliorate groundwater salinity.

ACKNOWLEDGEMENTS

The personnel of the International Association of Water Resources in the Southern Mediterranean Basin, Gafsa, Tunisia, deserves special recognition. The writers would also want to convey their appreciation to the numerous people who helped them put this paper together.

DATA AVAILABILITY STATEMENT

All data generated or analyzed during this study are included in this published article (and its supplementary information files).

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Table 1 The AHP approach is used to weight WQI parameters.

Step one

Step two

Step three

Step four

Objective

Criteria

Pair-wise comparison matrix

Weight for criteria

Reliability of AHP model (CI and CR)

Water quality classification

-Suitability parameters SAR

-Physicochemical parameter (EC-TDS-Na⁺-SO₄^2-and Cl^-)

Table 2 Comparison scale in AHP (Saaty 1980)

Intensity of importance	Signification
1	Equal importance of i and j (1)
3	Weak importance of i over j (2)
5	Strong importance of i over j (3)
7	Demonstrated importance of i over j (4)
9	Absolute importance of i over j (5)
2,4,6,8	Intermediate values the two adjacent judgments (6)

Table 3 Variation of the Random Index (RI) across 15 simulation runs (Saaty 2008)

N	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15
RI	0	0	0.58	0.90	1.12	1.24	1.32	1.141	1.45	1.49	1.51	1.48	1.56	1.57	1.58

Table 4 The classes of water quality according to the elements criterion (Ncibi et al. 2020)

Water quality	Excellent	Good	Permissible	Doubtful	Unsuitable
Criterion	Class1	Class2	Class3	Class4	Class5
EC	<250	250-750	750-2000	2000-3000	>3000
TDS	<1000	1000-2000	2000-3000	3000-4000	>4000
Cl^-	<142	142-249	249-426	426-710	>710
SO₄^2-	<192	192-336	336-575	575-960	>960
Na⁺	<69	69-200	200-252	-	>252
SAR	<10	10-18	18-26	-	>26
WQI	<2	2-3	3-4	4-5	>5

Table 5 Irrigation water quality classification criterion weights

Objectives

Criterion

Weight

Consistency ratio (CR)

Water quality index

EC

TDS

Chloride

Sulfate

Sodium

SAR

0.24

0.15

0.13

0.08

0.05

0.36

0.052

Groundwater quality delineation based on AHP method and GIS: a case study in Regueb basin, Central-Tunisia

Status:

Version 1

Abstract

Figures

Introduction

Study Area

Result And Discussion

Conclusion And Recommendations

Declarations

References

Tables

Status:

Version 1