ORIGINAL PAPER

Mapping recharge potential zones and natural rechargecalculation: study case in Sfax region

EmnaBoughariou & Salwa Saidi &Alae Eddine Barkaoui &Hafedh Khanfir & Yassin Zarehloul & Salem Bouri

Received: 14 March 2014 /Accepted: 11 June 2014# Saudi Society for Geosciences 2014

Abstract The groundwater constitutes the major water resourcein the study area of the current paper that is Sfax region. The latteris located in the south of Tunisia where the climate is arid. In fact,the natural groundwater recharge of the region is deeply affectedby the lack of precipitations which affects its natural groundwaterrecharge. The aim of the current paper is to define rechargepotential zones and to estimate the rainfall recharge of the shallowgroundwater. Henceforth, the potential recharge map wasestablished, based on the basin characteristics using lithology,topography, slope, and stream network parameters. Rechargeestimations were based on the numerical methods: the Estimationof Recharge in Overexploited Aquifers (Estimación de la Recargaen Acuíferos Sobreexplotados) (ERAS) numerical model, theSchoeller equation, the Fersi equations, and theDirectionGénéraledes Ressources en Eaux (General Administration of Water re-sources) (DGRE) coefficients. As a matter of fact, applying theFersi equations and the DGRE coefficients on the potential zonesallowed the deduction of a new spatial repartition of both favor-able and unfavorable recharge zones.

Keywords Recharge . Groundwater . Potential rechargezones . Arid regions . Sfax .Water resources . Geographicinformation system (GIS)

Abbreviations

PET Potential evapotranspirationWTF Water table fluctuationGIS Geographic information systemDEM Digital elevation modelR Recharge (mm/year)P Average of annual precipitations (mm/year)C1 Average concentration of chloride from rainfall (mg/l)C2 Average concentration of chloride from groundwater

(mg/l)Pi The annual rainfall (mm)Ri Annual recharge (mm)Ti The average air temperature in (°C)β Dimensionless calibration parameterM Calibrated parameterN Calibrated parameterI1 Efficient infiltration for moderate permeability (mm)I2 Efficient infiltration for low permeability

Introduction

Water resources are considered to be the most importantcomponents in arid regions where rainfall is low and evapo-transpiration is high (Tweed et al. 2011). This importance isespecially heightened in the case of high consumption wheregroundwater is exploited for agricultural and industrial activ-ities in addition to the urban use. Other factors can generallyinfluence the groundwater availability such as global warming(Woldeamlak et al. 2007; Carneiro et al. 2009; Piao et al.2010; Singh and Kumar 2010; Boughariou et al. 2013) andsea intrusion causing a variation in groundwater quantity andquality by salinization (Trabelsi et al. 2005; Cobaner et al.

E. Boughariou (*) : S. Saidi : S. BouriLaboratoire Eau, Energie et Environnement, ENIS, BP-W,3038 Sfax, Tunisiae-mail: boughariouemna@live.fr

A. E. Barkaoui :Y. ZarehloulFaculty of Science, University of Mohammed I, Oujda, Morocco

H. KhanfirARE, CRDA, Sfax, Tunisia

Arab J GeosciDOI 10.1007/s12517-014-1512-x

2012; Masciopinto 2013). Therefore, studying recharge inthese regions is required to estimate groundwater resources.

Besides, the recharge study is preventive for its quality(Carrera-Hernandez and Gaskin 2008) since recharge zonescould be linked to aquifer pollution or vulnerability (Saidiet al. 2010) as well as artificial recharge and water resourcesmanagement (Gotkowitz 2010; Rahman et al. 2012).

Among the most essential phases for groundwaterstudies to obtain the water budget is recharge calcula-tion. It is necessary to understand or even model theaquifer behavior. Different methods can be used toanalyze aquifer recharge such as direct measurement,water balance methods, Darcian approaches, tracer tech-niques, and empirical methods developed for particularcase studies (Lerner et al. 1990; Carrera-Hernandez andGaskin 2008). The analysis of water isotopes δ18O is

a reliable method yet it is not common in alllaboratories. Numerical models are also used todetermine aquifer recharge to name a few, Zoom Ob-ject-Oriented Distributed Recharge Model (ZOODRM)(Mansour and Hughes 2004) that is a numerical modelused to calculate the variations in potential rechargeused in several studies (Hughes et al. 2008; Campbellet al. 2010; Jackson et al. 2011). The previously statedmodel—ZOODRM—simulates indirect recharge that orig-inates from surface runoff applying the concepts of a soilmoisture field capacity plant root constants and wiltingpoints. In addition to the different parameters related tothe basin such as land surface elevation, land use, geology,soil type, rainfall, and PET to evaluate the proportion ofrainfall forming runoff, this model requires data aboutvegetation types, roots, and seasonal growth rates. The

Fig. 1 Location of the study area

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collect of a large database for this model is necessary, butsometimes it cannot be granted. Recharge can also becalculated based on groundwater hydraulic heads such asWTF method (Sophocleous 1991) where the mean

annual fluctuation of the aquifer is carefully calculated foreach observation on a long temporal period. This paperdefines the recharge potential zones (Kumar and Kumar2011; Gaura et al. 2011; Abdalla 2012) based on

Fig. 2 Study area lithology map

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regional characteristics using ArcGIS (ESRI 1997). Re-charge was also calculated by different methods and com-pared for a better estimation of the study area waterresources.

Study area

Sfax water resources are considered as one of the mostexploited in Tunisia because of the region’s high demographyand diverse economic and agricultural activities. Being acoastal city (Fig. 1), Sfax groundwater is threatened by seaintrusion. Besides, overconsumption is due to agriculturaldemands mostly for olive and vegetable crops added to

domestic and industrial consumption in the city. Geographi-cally, the study area is a part of eastern Tunisia and is locatedbetween 34° 10′ 16.47 N to 35° 17′ 20.14 N latitude and 9° 54′53.35 E to 10°46′ 47.76 E longitude with a total area of6,848 km2. Administratively, this region is limited by the seaon the east, on the north by Mahdia region, on the west byKairouan region and Sidi Bouzid, and byGabes regions on thesouth. The lithology of the study area (Fig. 2) is dominated bythe outcrops of Miocene, Pliocene, and Quaternary with adomination of sandy and sandy clay soil nature. The streamnetwork (Fig. 3) is developed in Sfax with major wadies likewadi El Maou, wadi Chaffar, and wadi Lben. This streamnetwork has temporary activity related to the pouring rain ofthe arid climate. As for the climate, it is arid with large

Fig. 3 Study area stream networkmap

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temperature and rainfall variations. Average annual tempera-ture and rainfall are about 19.5 °C and 224 mm, respectively.

Sfax aquifer thickness varies between 10 and 150 m: in thenorth, it is about 130 m in El Amra, 150 m in sebkhat ElGhorra, and meanwhile, it is around 75 m in the western partand tends to get thin in the center with 50 m in Sidi Salah(Trabelsi 2008). Its recharge is basically made by rainfallinfiltration, water irrigation, and domestic rejections on theurban part.

Methodology

The groundwater potential zones have been identifiedthrough spatial data model of ArcGIS (ESRI 1997)using different parameters of the basin (Gaura et al.2011) which are the slope, topography, stream network,and lithology as used in the available literature (Sikdaret al. 2004; Abdalla 2012). It is noteworthy that thelineament parameter is not used for this study areabecause the Quaternary shallow aquifer is not affectedby faults. Each parameter has in fact been integrated tothe GIS model as a thematic map such as in multi-criteria evaluation (MCE) (Voogd 1983).

To obtain the final map of groundwater potential zones, theweights were assigned to those thematic maps according to

each parameter. The weights as used in literature represent theimportance in groundwater potential zone (Gaura et al. 2011)and its strength of influence/contribution with respect to thegroundwater storing (Abdalla 2012). Thus, for each parame-ter, the thematic maps were also classified into three numericclasses from 1 to 3 where 3 is the most favorable assigned forthe highest contribution and 1 is the least related to the lowestcontribution for recharge (Table 1).

Slope

Slope is considered to be one of the influential parameters onthe quantity of percolation and infiltration water. Actually, asteep slope makes percolation easier and cannot be favorablefor vertical water infiltration. On the other hand, a flat areahaving low slope is favorable for water collection and infil-tration and consequently increases recharge rates. “Geomor-phological maps were developed from remote sensing images.Slope is one of the main factors in the selection of floodspreading areas. On steep slopes, runoff is more erosive andcan more easily transport loose sediments down slope”(Ghayoumiana and Saravib 2007).

Therefore, a slope density map is made using ArcGIS andDEM which are available from ASTER Global Digital Eleva-tion Model (ASTER GDEM 2014). This map shows a slope

Table 1 Thematic map weightsand class range ranks Thematic layer Map weight Class ranges Degree Rank

Slope density 2 0–0.5 High 3

0.5–1 Moderate 2

1–0.365 Low 1

Topograhy 3 −43–100 High 3

100–200 Moderate 2

200–540 Low 1

Stream network density 3 0–1 Low 3

1–2 Moderate 2

2–3.7 High 1

Lithology 3 Clay and sand Moderate 2

Limestone and marl Low 1

Oolitic limestone and bioclastic High 3

Encrusting calcareous High 3

Alluvial fans High 3

phosphogypsum Low 1

Sand High 3

Limon gypsum Low 1

Silty sand Moderate 2

Vegetation Moderate 2

Water body Moderate 2

Urban area Low 1

Soil High 3

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ranging from 0 to 3.657 (Fig. 4). Since the infiltration isinversely related to the slope degree, the ranks of the threedegree classes of the slope thematic map (Fig. 5) are rangingfrom 1 to 3 where the highest rank is attributed to the lowestclass where slope is not dense. The lowest rank 1 is attributedto the highest class with the dense slope unfavorable forrecharge.

Lithology

Lithology is one of the most important parameters used forrecharge calculation. In fact, this parameter is automatically

linked to conductivity which is widely used in recharge cal-culation equations in this study area.

In reality, many studies used the “indicator kriging” relatedto soil texture and permeability to define groundwater re-charge zones (Castrignanò et al. 2000; Fogg et al. 1999;Guadagnini et al. 2002; Johnson and Dreiss 1989; Pohlmannet al. 2000; Trevisani and Fabbri 2010; Jang et al. 2013) since“the condition of soil textures is closely related to subsoilinfiltration and unsaturated soil percolation, and it is the mostimportant factor to dominate aquifer recharge” (Jang et al.2013).

This parameter reflects the rainfall infiltration degreefor the nature of each soil. The lithology map is used

Fig. 4 Slope degree map fromASTER GDEM

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from CRDA (2010) showing clay and sand, limestoneand marl, oolitic limestone and bioclastic, encrustingcalcareous, alluvial fans, alluvial wadis, phosphogypsumsand, limon gypsum, and silty sand. The classificationis based on conductivity values from literature (Morrisand Johnson 1967; Freeze and Cherry 1979; Castany1982; Banton and Bangoy 1997; Smida 2008) in addi-tion to CRDA permeability index attributes to eachlithological nature.

Thereby, the less permeable grounds with a fine ornonfractured lithology such as clay and gypsum are rankedby the lowest number while the highest rank is attributed to thefields having a better permeability. The lithology class map

(Fig. 6) indicates that the majority of the study area is repre-sented by the medium class.

Topography

In addition to slope map, the topographic map is also takeninto consideration in this paper since it classifies the regioninto three areas going from a high altitude favorable to runoffzones to low-altitude zones where infiltration rises. Focused(localized) recharge occurs at topographic depressions such asstreams and lakes (Scanlon et al. 2002; Carrera-Hernandezand Gaskin 2008). The topographic map ranges from 0 to

Fig. 5 Slope classes

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540 m where the altitude is increasing from the eastern coastto the west and it shows a dome on the western part. Accord-ing to this map, we can classify the study area into threeclasses where the rank 3 is attributed to the low class, 2 tothe moderate, and 1 to the highest topography class (Fig. 7).

Stream network

Stream network is one of the most common parametersused for recharge evaluation since it is directly linked to

the runoff and infiltration relationship. Actually, thestream network contributes in the favor of runoff in thewater budget. It is generally assumed that, in humidregions, groundwater recharge is predominantly diffusein space, since rainfall is greater than evapotranspirationand the vadose zone is small, which favors direct perco-lation through the soil (Dages et al. 2009). In this paper,the stream network of the study area is represented by itsdensity map (Fig. 8) which is composed of three classes,high, moderate, and low stream network density, and theattributed ranks are respectively 1, 2, and 3.

Fig. 6 Lithologic classes

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The classified maps are also given an important positionaccording to Abdalla (2012) where each thematic map has beengiven a weight value related to its influence with respect to thegroundwater storing since the study area in this situation is notvery different from a lithological and morphological perspec-tive. Therefore, the attributed weights of each map are 2 forslope, while topography, stream network, and lithology have ahigher weight which is 3.

As a final step, all the thematic layers have been overlaidand mathematically calculated in one single operation usingthe raster calculator function on ArcGIS model where

classified maps are multiplied by their weights then summed.

Calculated map ¼ 2 � slope map þ 3 � topography map

þ 3 � stream network map

þ 3 � lithology map

The potential recharge zones map (Fig. 9), dividedinto three equal intervals, mostly shows a high potential.The low-potential zones are focused on the high-altitudearea, where the topography is important and the slope is

Fig. 7 Topography classes

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steep which makes those spots favorable to the runoff.The high-potential zones are located in the bottom ofthose high areas where water is collected downstream.This paper is based on different methodologies thatestimate in turn potential aquifer recharge through sim-ple equations and consider different parameters such asrecharge potential zones map, soil units, climatologicalvariables such as rainfall and temperature, and chloridemeasurements.

Natural recharge calculation

Chloride method

The aquifer recharge can be calculated using a single equation(Schoeller equation) based on chloride balance according to

the law of conservation of mass. Actually, the burden ofconservative element, which is the chloride, in the inputfunction representing the amount of total precipitation P isequal to the one of the output function which is the recharge R(DASSI 2004). Therefore,

P :C1 ¼ R : C2 ð1ÞR ¼ P : C1=C2 ð2Þ

where P is the average of annual precipitations (mm/year), C1is the average concentration of chloride from rainfall (mg/l),and C2 is the average concentration of chloride from ground-water (mg/l).

Using a single value from el Maou station for theperiod of 1950–2012 which is 224 mm/year, 22 mg/lfor C, and 975 mg/l for C2, the average recharge for

Fig. 8 Stream network density

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the whole region is about 5 mm/year:

R ¼ 224 � 22=975

R ¼ 5 mm=year

This method was also used according to the rainfall spatialvariation where the study area is divided into three regionsshowing high rainfall in the northern part and low rainfall inthe south (Fig. 10). The resulting map is composed necessarily

of three recharge regions with an average of 4.9 mm/yearwhere the recharge is evolving in parallel with the rainfallrates (Fig. 11).

ERAS method

Other equations could be used to determine the recharge ratesfor the study area without taking into consideration aquifercharacteristics. One of those equations is Estimation of Re-charge in Overexploited Aquifers" (Estimación de la Recarga

Fig. 9 Potential recharge zonesmap

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en Acuíferos Sobreexplotados) ERAS numerical model(Murillo and Roncero 2005; Aguilera and Murillo 2009;Andreu et al. 2011):

Ri ¼ M � Pi − Tiβ� �N ð3Þ

where Pi is the annual rainfall (mm) and Ti is the average airtemperature (°C).

β is a dimensionless calibration parameter forconverting temperature into potential evapotranspiration.It ranges from 1.3 for cold zones to 1.6 for warmer zones(MMA 2000). The choice of the parameters was based onprevious studies (Andreu et al. 2001). The most suitablevalues for M are 0.01 and 0.06 while the possible valuesof N corresponding to the study area elevation are 1.22

and 0.9. Since β depends on the climate temperature,several combinations were established as shown in Table 1with both the maximum and minimum values of theannual precipitation. Finally, the values of 0.9, 0.06, and1.5 are considered to be the most appropriate for N, M,and β parameters because of the conditions’ similaritiesfor both study regions (Table 2). The calculated map(Fig. 12) shows recharge rate varying between 4.42 and5.25 mm/year with an average of 4.8 mm/year.

Fersi

Fersi’s equations (Ben Brahim 2006; Smida 2003) are some ofthe most used equations in Sfax and in the south of Tunisia.They depend on mean annual rainfall rates and basin

Fig. 10 Average rainfall map

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permeability index. Therefore, two efficient infiltration valuesare calculated for moderate and low-permeability index:

I l ¼ 5=100ð Þ � P½ � − 3:4 ð4Þ

I2 ¼ 2; 5=100ð Þ � P½ � − 4:6 ð5Þ

where I1 is the efficient infiltration for moderate permeability(mm), I2 is the efficient infiltration for low permeability, and Pis the average of annual precipitations (mm/year).

The existence of two equations for three classes in therecharge potential zones map required a new classification.Therefore, it has been reclassified into two classes. Then, the

Fig. 11 Recharge calculationbased on Schoeller equation

Table 2 Recharge calculation based on ERAS numerical model with a variation of N, M, and β

N=1.22 N=0.9

M=0.01 M=0.06 M=0.01 M=0.06

β R (mm/year) forP=205 mm

R (mm/year) forP=230 mm

R (mm/year) forP=205 mm

R (mm/year) forP=230 mm

R (mm/year) forP=205 mm

R (mm/year) forP=230 mm

R (mm/year) forP=205 mm

R (mm/year) forP=230 mm

1.3 4.79 5.74 28.75 34.42 0.95 1.08 5.70 6.50

1.4 4.18 5.11 25.13 30.67 0.86 1.00 5.16 5.97

1.5 3.40 4.29 20.41 25.76 0.74 0.88 4.42 5.25

1.6 2.39 3.24 14.36 19.41 0.57 0.71 3.41 4.26

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equations were applied into those two classes according to thespatial variation of the precipitation to end up with threeintervals of recharge as shown in the map (Fig. 13): highrecharge rate (from 7 to 8.5 mm/year), moderate recharge rate(from 6 to 7 mm/year), and low recharge rate (from 0.5 to1.5 mm/year) with an average recharge of 5.7 mm/year.

DGRE

Recharge is also calculated in this area using Direction Généraledes Ressources en Eaux ( General Administration of Water re-sources) (DGRE) indexes (Trabelsi 2008)where efficient rechargeis a percentage of the precipitations, depending on the permeabilityof the ground of the studied basin: 6 % for high permeability, 4 %for moderate permeability, and 2% for low permeability (Trabelsi2008; Smida 2008).

As used in previous studies, those coefficients are used tocalculate recharge from the rainfall variation map and

permeability map which is a result of the lithologic map. Asa result, four intervals of recharge are illustrated in the re-charge map (Fig. 14): the lowest interval starts with a value of4 to 5 mm/year, the second interval from 7 to 8.5 mm/year, thethird from 8.5 to 10 mm/year, and the forth from 12 to 14 mm/year. The main recharge value is 10.14/year.

The same method and the same coefficients are applied tothe recharge potential zones map. However, in this case, thehighest coefficient is attributed for the high potential areawhile 2 % is considered for the lowest potential area. Thecalculated map (Fig. 15) presents the same four intervals but adifferent spatial variation.

Results and discussion

The recharge potential zones map is a result of over-laying several parameters according to their influence

Fig. 12 Recharge calculationbased on ERAS numerical model

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and impact on water infiltration. This map shows spatialvariation of recharge potential where low potential areasare corresponding to high slope density class and highpotential is located in the coast, the northeastern partand at the depressions at the foothills. In this model,the soil elevation is taken into consideration with theslope density map and the topography map which ex-plains the similarity between low potential area and thesteep slope regions. The lowest potential is also corre-sponding to the highest stream density which is also aresult of slope spatial variation since it is favorable forrunoff. The recharge potential zone map is on the otherhand different from the lithologic and permeabilitymaps which are similar to lithology class map, and thatdifference has a greater influence on calculated potentialrecharge map.

The chloride method is a numerical method based onchloride concentration in rainfall and aquifer water inaddition to the rainfall measurement. Calculating thepotential recharge according to the precipitation

variation and spatial variation on the study area leadsto a mean value of 4.9 mm/year. This value is almostthe same as the one resulted from ERAS numericalmodel which map presents the same zones adequatelyto precipitations’ map. Even the maximum and mini-mum values are close. This proves both maps’convergence.

Once the basin characteristics collected in two classesof recharge potential zones map are employed in addi-tion to the space repartition of precipitations, the poten-tial recharge map shows a different repartition in thestudy area. Actually, Fersi equations shows low rechargein the low-potential zones while three other areas aredistinguished: medium recharge located in the south ofthe study area and in the center of coastal zone with aninterval going from 6.1 up to 7 mm/year while themajority of the basin has high recharge rate rangingfrom 7 up to 8.5 mm/year.

The three classes of recharge potential zones map, whenusing the DGRE coefficients and the rainfall spatial

Fig. 13 Recharge calculationaccording to recharge potentialzones based on Fersi equation

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repartition, lead to four intervals that are higher than theones of Fersi equation map even though these regions havesome similarities. However, the regions of moderate po-tential areas are divided into two different recharge inter-vals: the lower one is located on the southern part, whilethe higher one is in the center of the study area. As usingthe same coefficient values to calculate recharge accordingto the permeability classes, the recharge intervals are thesame but the 8.5–10 mm/year interval is much more dom-inant; spatial variation is less obvious in the potentialzones. The high recharge rate regions are limited in spacein the favor of moderate recharge. The 7–8.5 mm/yearinterval is more developed in the central part comparingto the recharge obtained from the potential zones map.However, it is smaller on the southern part.

Regardless of spatial location of the recharge zones, theaverage of DGRE coefficients’ calculation (10.14 mm/year) isalmost much higher than Fersi’s (5.7 mm/year) which is closer

to ERAS and chloride method calculations (4.8 and 4.9 mm/year respectively).

Applying Fersi’s equations to estimate recharge in thepotential zones seems to be the best method among the onesused in this paper since its coefficients are more realistic andits calculation takes the basin characteristics into considerationin addition to the rainfall space variation.

Conclusion

In arid regions where surface water resources and rain-falls are limited, the shallow groundwater recharge isquite important. This paper puts focus on the rechargepotential zones. These zones are determined using fourparameters. First, the parameters are used to calculatethe recharge instead of the permeability map of Fersiand DGRE coefficients. Then, the results were

Fig. 14 Recharge calculationaccording to lithology based onDGRE coefficients

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compared to ERAS and Schoeller equations. Next, thedifferent methods led to a spatial variation and differentrecharge intervals. Finally, it is worth noting that thesemethods omit other important parameters in arid areassuch as soil occupation and evapotranspiration. Besides,numerical models based on other software such asZOODRM (Mansour and Hughes 2004) and DiCaSM(Ragab et al. 2010) require more specific database andmuch more parameters at the level of the input. Thenumerical models can also be of a great help for thegeodynamic modeling when it comes to aquifer behav-ior for recent situations or conditional ones. Be that asit may, the potential zones maps could be used eitherfor recharge calculation or by governmental administra-tors. Once compared with the consumption panel, thepotential zones maps are substantial to make decisionsabout wells creation, industrial pollution, and agricultur-al activities which constitute a real threat in case of agood recharge potential zone.

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