Environ Earth Sci (2010) 59:1579–1588 DOI 10.1007/s12665-009-0143-0

ORIGINAL ARTICLE

Groundwater vulnerability and risk mapping of the Hajeb-jelma aquifer (Central Tunisia) using a GIS-based DRASTIC model Salwa Saidi Æ Salem Bouri Æ Hamed Ben Dhia

Received: 3 January 2008 / Accepted: 26 February 2009 / Published online: 20 March 2009 Ó Springer-Verlag 2009

Abstract The aim of this study is to elaborate a synthetic document for the assessment of groundwater vulnerability to pollution in the Hajeb-Jelma aquifer. The specific object is to incorporate the Geographical Information System (GIS) to generate groundwater vulnerability and risk maps with DRASTIC model. Indeed, GIS could help to make the results of a complicated model more clear through visual representation, providing an applicable tool for decision makers. The vulnerability map of Hajeb-Jelma watershed shows three classes: moderate, high and very high depending on the intrinsic properties. The risk map shows a very high risk dependant on hydrogeological characteristics, land use and human impacts in major part of the Hajeb-Jelma region. These maps could serve as a scientific basis for sustainable land use planning and groundwater management in the Hajeb-Jelma region. Keywords Hajeb-Jelma groundwater
DRASTIC model
Vulnerability
Pollution
Risk map
Aquifer

Introduction Groundwater is a natural drinking water resource often subjected to severe human impacts. Several programs and

Electronic supplementary material The online version of this article (doi:10.1007/s12665-009-0143-0) contains supplementary material, which is available to authorized users. S. Saidi
S. Bouri (&)
H. Ben Dhia Laboratoire de recherche Eau- Environnement et Energie (LR3E), Ecole Nationale d’Inge´nieurs de Sfax (ENIS), B.p.w.3038, Sfax, Tunisia e-mail: [email protected]

models required preserving optimum groundwater quality, and so management of this vital natural resource has become a worldwide priority. The increasing use of chemical fertilizers and the overexploitation of HajebJelma aquifer during the last decades were the main causes of the pollution of the groundwater. Thus, a vulnerability map to pollution of the Hajeb-Jelma aquifer is highly needed. Along the time, hydrogeological studies undertaken in various regions showed an evolution of the vulnerability concept. In the late 1960s, the French hydrogeologist Margat defined the term ‘‘intrinsic vulnerability’’ of an aquifer as the ease with which a contaminant introduced into the groundwater surface can reach and diffuse in groundwater (Margat 1968; Vrba and Zaporozec 1994). Another definition was evoked by Labo-Ferreira and Cabral (1991) who considered groundwater vulnerability to pollution as ‘‘the sensitivity of groundwater quality to an imposed contaminant load, which is determined by the intrinsic vulnerability of the aquifer’’. Obviously, groundwater vulnerability mapping is based on the idea that some land areas are more vulnerable to groundwater contamination than others. The assessment of groundwater vulnerability to pollution has been the subject to intensive research during the past years and a variety of methods have been developed. Focusing on Hajeb-Jelma area, this paper attempts to elaborate groundwater vulnerability and risk maps. These latter aimed to show areas of greatest potential for groundwater contamination on the basis of hydrogeological conditions and human impacts. A geographical information system (GIS) is used to create the groundwater vulnerability map by overlaying the available hydrogeological data.

123

1580

Environ Earth Sci (2010) 59:1579–1588

how much likely it is that a site will be contaminated and how the contaminant moves from the site of contamination to the aquifer. In fact, vulnerability rating or DRASTIC index would be determined for these reasons. DRASTIC is a method developed by the US Environmental Protection Agency (USEPA) to provide a systematic evaluation of the potential for groundwater contamination that is consistent with a national basis (Aller et al. 1987 in Michaud et al. 2003). In this method, spatial datasets on depth to groundwater (D), recharge (R), aquifer type (A), soil properties (S), topography (T), impact of the vadose zone (I) and the hydraulic conductivity (C) are combined. A DRASTIC index or vulnerability rating can be obtained from these parameters. Higher sum values represent a greater potential for pollution or a greater vulnerability of the aquifer to contamination. For a particular area being evaluated, each factor is rated on a scale from 1 to 10 indicating the relative pollution potential of that factor for that area. Once each factor has been assigned a rating, it is weighted. Weight values, from 1 to 5, express the relative importance of the factors with respect to each other. Finally, the total impact factor score, the DRASTIC index number, can be calculated:

Study area The Hajeb-Jelma Basin is located in the northern part of Central Tunisia and has a total surface of 1,350 km2 (Fig. 1). This region is characterized by an arid climate with large temperature and rainfall variations. Average annual temperature and rainfall are about 19°C and 230 mm, respectively (INM 2005). In addition, it is characterized by a high evaporation accentuated by ‘‘sirocco’’, hot dry summers and cold winters. The Hajeb-Jelma aquifer has the same boundaries as the inner hydrogeologic catchments. It is located in Mio-PlioQuaternary layer system, which is constituted mainly by sand and silty clay. The groundwater has an estimated safe yield of 24.5 106 m3/year (SONEDE 2005 and RAAD 2005), but where annual abstraction stands at 19.5 106 m3/ year (RAAD 2005). This positive assessment is due to the almost total of wastewater which is infiltrated in the aquifer through improperly completed or abandoned water wells. Materials and methods Description of the GIS model association

DRASTIC index ¼ Dr Dw þ Rr Rw þ Ar Aw þ Sr Sw þ Tr Tw þ Ir Iw þ Cr Cw

Numerous approaches can be considered to model groundwater vulnerability. A comprehensive groundwater vulnerability model must include parameters to describe

where w is weight and r is rank

Fig. 1 Localization of the study area

Labeid montain

Hajeb el Ayoun Mrhila montain

Zaouia-Iroua mountain

Jelma

Lessouada mountain

0

10 Km

Quaternary

Turonian (Dolomitic limestone)

Mio-Pliocene

LowerTuronian -Cénomanian

Oligocene (massive graves)

Albian (dolomitic limestone )

calcareous lutetian

Aptian (limestone,marl, graves)

Campanian-Maastrichian (White limestone )

Triasic clay and gypsum

Coniacian (limestone )

other outcrops

Study area boundary

123

Hamra Koumine mountain

Environ Earth Sci (2010) 59:1579–1588

1581

This method considers intrinsic vulnerability, taking into account the hydrogeological characteristics of the area, but is independent of the nature of the contaminants. Data input is facilitated by a GIS–model interface. The main GIS softwares used in this study are Arc view and Arc info. In this case, DRASTIC model is developed within a GIS. The method and the GIS may also present a common interface where information is automatically transferred from one software to the other. Indeed, GIS can combine many data sets and display them in a common framework as thematic map to be utilized by DRASTIC model. The GIS is also used to convert these maps to raster mode. The conversion consists in the fragmentation of a map into a series of pixels whose size is 300 m 9 300 m (Fig. 7, ESM). A numerical value can be attributed to each pixel. The resulting grid corresponds to a support for the seven parameters of DRASTIC. Thus, the vulnerability is calculated for each pixel implicating a high resolution. The GIS is also used to elaborate the groundwater vulnerability map by overlaying the seven thematic maps.

samples (Saidi 2006) to update the old data. Table 1 summarizes GIS pre-processing and manipulation techniques used to create seven input data layers for the DRASTIC index. Modification of the DRASTIC method For the assessment of pollution potential in this study, a modification of the DRASTIC method is proposed. The modification procedure involves the aquifer media (A) and the impact of the vadose zone (I) parameters. In fact, in this case of study some of the soil classes cannot be found in the table of Aller et al. (1987) classification and widely, heterogeneity of lithology is detected both in the aquifer and the vadose zone. For these two reasons, the permeability values are implicated to substitute lithology ones (Table 2). Development of the DRASTIC vulnerability index Depth to groundwater (D)

Compiling database for the DRASTIC index A multidisciplinary data bank is highly needed for this approach. In fact, a range of data are required in order to provide quantitative information for the groundwater vulnerability assessment, including the distribution of soil types, depth to groundwater and the spatial rainfall. These data are taken from geological studies (Koschel 1980; El Ghali 1992), hydrogeological studies (Koschel 1980; Zouari 1998; District of the Water Resources ‘‘DWR’’ of Sidi Bouzid 2004, 2005), a climatologic study (Institut de la Me´te´orologie Nationale ‘‘INM’’), and soil studies (Agricultural map obtained from the Regional Agency of Agricultural Development ‘‘RAAD’’ of Sidi Bouzid 2004). These data, derived from a variety of sources, are also obtained in a range of formats such as paper and numerical files. A field survey was carried out in February 2006 in order to measure piezometric level and collect groundwater

Depth to groundwater values varies between 3 and 30 m (Saidi 2006). The depth index is obtained as a result of multiplying Dr 9 Dw based on the weighting of Aller et al. (1987) (Table 2; Fig. 2; Fig. 8, ESM). A low water depth will lead to higher vulnerability rating. Indeed, the western part of the study area is considered the most vulnerable according to this parameter. Recharge (R) Based on the annual rainfall data and applied irrigation volumes measured in the study area and calculated for the period (1974–2005), the recharge values using the watertable fluctuations (WTF) method. The WTF estimates groundwater recharge as the product of specific yield and the annual rate of water-table rise, including the total groundwater draft (Sophocleous 1991). This method was

Table 1 Evaluation of the parameters taken from the processing data DRASTIC parameters

Type of data

Mode of processing

Topography

Topographic charts with the 1/50,000: sheets N°77, 78, 85, 86, 70, 94 RAAD (2004)

Digitalization

Rainfall distribution

Annual rainfall data during the period 1974–2005 (INM 2005)

Interpolation

Soil type Well locations and depth to Groundwater

Soil map RAAD (2004) Static level statement of the year 2006 (Saidi 2006)

Digitalization Interpolation

Aquifer media

Equivalent permeability taken from well logs (DWR)

Interpolation

Lithology of the vadoze zone

Equivalent permeability taken from well logs (DWR)

Interpolation

Conductivity (Hydraulic)

Permeability calculated from the transmissivities taken from the pumping tests (DWR)

Interpolation

123

1582

Environ Earth Sci (2010) 59:1579–1588

Table 2 Rank and weight of the seven DRASTIC parameters (Aller et al. 1987) Depth to water (m)

Net recharge (m)

Interval

R Interval

3–4.5

9

4.5–9

7 [0.25

9–15

5

15–23

3

23–31

2

Topography (slope) (%) R Interval

0.17–0.25 8

Weight 4

Weight 5

9

R

Hydraulic conductivity (m/s) Interval

Aquifer media

R Permeability classes

Impact of the vadose zone R Permeability classes

R Pedologic classes

R

1

confined Aquifer (K = 1.6 9 10-9 to 10-5)

1

Mineral soil

9

Clay, sand and calcareous (K = 10-5 to 10-3)

5

Isohumic chestnut soil

8

6

Rendzina

7

Calcareous brown soil

6

Soil with little evolution

5

0–3%

10 5 9 10-5 to 2 2 9 10-4

3–5%

9

2 9 10-4 to 4 4 10-4

2 Massive clay and sand (5–15 9 10-5)

5–10%

5

4 9 10-4 to 6 5 9 10-4

Sand, gravel and clay (15–45 9 10-5)

4

Sand, silt and gravel (10-3 to 10-2)

10–15%

3

Weight 3

Sand and gravel (45–450 9 10-5)

8

Weight 5

Sand and clay (1.5–5 9 10-5)

Soil media

Weight 3 Weight 1

Polygenetic soil

4

Gypsum soil

3

Halomorphic soil 2 Urbain zones

1

Weight 2 R rank

proved to be particularly appropriate when water levels show a quick response in areas with a relatively thin vadose zone (Moon et al. 2004), which is the case for Hajeb-Jemla aquifer. Computed annual recharge values varied between 217 and 287 mm. The resulting map of rainfall distribution is elaborated by interpolation. Then it is classified and multiplied by the weighting factor of the recharge parameter as shown in Table 2 and (Fig. 3; Fig. 9, ESM). The amount of recharge is positively correlated with the vulnerability rating.

Topography (T)

Aquifer media (A)

This parameter is represented by the equivalent permeability which is found in well logs from DWR. Vertical equivalent permeability values are between 10-2 and 10-4 m/s. It has a rating between 1 and 6 and affected by a weight of 5 (Table 2; Fig. 4; Fig. 16, ESM).

This parameter is represented by the equivalent permeability which is found in well logs (DWR 2005). Horizontal equivalent permeability values are between 1.5 9 10-5 and 45 9 10-4 m/s. It has a rating between 1 and 8 and affected by a weight of 3 (Table 2; Figs. 10, 11, ESM). Soil media (S) Nine soil classes are extracted (Fig. 12, ESM) and to each one a rating value is attributed. The vector layer of soil is converted to a raster grid and multiplied by the weighting factor of the soil media (2) which has produced the map of Sr 9 Sw as shown in (Fig. 13, ESM).

123

The surface slope is calculated using five topographic maps (1/50,000 scale) covering the study area. It is elaborated within 3D analyst function of Arc View GIS (Fig. 14, ESM). Then, the slope index is reclassified and converted into grid coverage and multiplied by the topographic weight as shown in Fig. 15, ESM. Impact of the vadose zone (I)

Hydraulic conductivity (C) The hydraulic conductivity of the Hajeb-Jelma aquifer is calculated based on the following equation: K = T/b, where k is the hydraulic conductivity of the aquifer (m/s), T is the transmissivity (m2/s), and b is the thickness of the aquifer expressed in m. The hydraulic conductivity map (Fig. 17, ESM only), obtained by interpolation, is converted to a raster grid and multiplied by the weighting

Environ Earth Sci (2010) 59:1579–1588

1583

Fig. 2 Depth to groundwater map (Saidi 2006)

Fig. 3 Recharge map

factor (3). The latter has produced the map of Cr 9 Cw as shown in Fig. 18, ESM. The DRASTIC vulnerability index All the GIS coverage is in raster format and values for each overlay are summed in Arc View GIS according to the

pixel value of each area that resulted from multiplying the ratings with its appropriate DRASTIC weight (Table 2). The resulting DRASTIC values lay between 168 and 216 (Fig. 18, ESM). This range is classified on the basis of the above classification as: (1) 168–179, which is assigned a moderate vulnerability, (2) 180–199, is represented by a high vulnerability and (3) 200–216, which is assigned a

123

1584

Environ Earth Sci (2010) 59:1579–1588

Fig. 4 Permeability of the vadose zone map

2.

Table 3 DRASTIC index (Aller et al. 1987) Interval

DRASTIC

168–179

3

180–199

2

200–216

1

The value of both indicators implicates that the use of the resource is sustainable but it is in crucial issue and the state is more drastic in dry periods. 3.

very high vulnerability (Table 3). Thanks to the Digital Terrain Model (DTM), using 3D analyst extension of Arc GIS, you can obtain a good visualization of the different vulnerability classes (Fig. 5). Socio-economic value of groundwater Socio-economic vulnerability is seen as the integration across a range of stresses and across a range of human capacities. It involves groundwater accessibility, exploitability and use. Economic value integrates specially groundwater extraction of drinking and agricultural. Proposed indicators described socio-economic value of groundwater and based on the aggregation of selected variables both quantitative and qualitative (Zaporozec 2002) are calculated. These variables are defined as: 1.

Groundwater recharge/total extraction 9 100 in this case of study it is 125.64%.

123

Total extraction/available resources 9 100. In such a case the indicator is 80%.

4.

Variation in storage: the comparison between the two states of 1995 and 2006 (Figs. 20, 21, ESM) shows a decline of the piezometric level reaching 15 m, which is registered in the North East and the South of the study area. This index reveals an overexploitation observed in the East of the Hajeb-Jelma phreatic aquifer. In addition, in the same zone a loss of water with high quality (TDS \ 0.6 g/l) is detected. In fact this ‘‘mineral water’’ is used to irrigate crops and thus is demonstrated by the declining of the water salinity in the extreme North East of the region, between 1973 and 2006 states (Figs. 22, 23, ESM), whereas people can exploit this water to cover the needs of water drinking in stressed zones. Groundwater quality: water supply is under threat as a result of salinization by scrubbing Triasic outcrops salts where the salinity exceeds 7 g/l (Saidi 2006). The Piper diagram shows three facies which are chloridric, sodic and sulphidic (Fig. 24, ESM). The Scholler diagram indicates heterogeneous water-type. Indeed,

Environ Earth Sci (2010) 59:1579–1588

1585

Fig. 5 Vulnerability map

two groups are identified (Fig. 25, ESM): the first one is dominated by Cl and Na, whereas the second is highly concentrated in SO4. Therefore, the high salinity and sulfuric concentration can cause the decrease of Hajeb-Jelma resources quality. In addition, the salinity map (Fig 23, ESM) which presents the present state of the aquifer shows a decreasing tendency in the North East and the South. The nitrate map reveals the same tendency of the salinity ones (Figs. 23, 30, ESM).In order to demonstrate if the water resources are threatened by anthropogenic factors, two selective indicators are calculated: P – areas with groundwater depletion problems/total study area is 45% P – areas with groundwater natural quality problems/ total studied area is 25%

subsurface environment (Ferreira and Oliveira 1997). The risk of pollution is determined both by the intrinsic characteristics of the aquifer, which are relatively static, and the existence of potentially polluting activities, which are dynamic factors that can be changed and controlled.

Considering the quantity and quality indicators, the use of resource is sustainable. But, the increase of water wells and fertilizers applications can raise the pressure on the Hajeb-Jelma aquifer. In addition, the water storage of Hajeb-Jelma is exposed to a variety of stresses and threats that water managers adapt to.

MDðiÞ ¼ DI þ Lr  Lw

Risk map using land use map and DRASTIC vulnerability map To evaluate potential risk, an additional parameter could be integrated, which is the land use (Fig. 26, ESM). In order to introduce a land use factor into the DRASTIC index, the land use map is rated according to the Secunda et al. (1998) (Table 4). This map is converted into a raster grid and is multiplied by the weight of the parameter (Lw = 5) (Fig. 27, ESM). The resultant grid coverage is then added to the DRASTIC index based on the equation (Secunda et al. 1998).

where DI is the DRASTIC index and Lr 9 Lw is the land use index, the modified DRASTIC index is subdivided into two classes (1) 193–199 with high risk and (2) 200–256 with very high risk (Fig. 28, ESM).

Development of the DRASTIC risk assessment

Risk map using hazard map and DRASTIC vulnerability map

Vulnerability is distinct from pollution risk which depends not only on hydrogeological conditions but also on the existence of significant pollutant loading entering the

In this method, risk assessment includes all activities that consider the possible origins of contamination. The points

123

1586

Environ Earth Sci (2010) 59:1579–1588

Table 4 Land use categories for the study area and the weight of this parameter (Secunda et al. 1998 in Adamat et al. 2003) Land use category

Lr

Built up area

8

Irrigated field crops

8

Uncultivated land

5

Lw

5

of potential contamination release are determined with hazard assessment where all possible origins of contamination and likelihood of its release are considered (Andreo et al. 2005). In order to attain the risk assessment we could overlay the hazard map (Fig. 29, ESM) and the vulnerability map (Fig. 5). Despite differences between the two risk maps (Fig. 28, ESM; Fig. 6), both methods classify the zone where anthropogenic activities are concentrated as zone of very high risk. Validation of the intrinsic vulnerability maps Aquifer vulnerability method requires validation to reduce subjectivity in the selection of rating and to increase Fig. 6 The risk map made by overlaying the vulnerability and the hazardous maps

123

reliability (Ramos-Leal and Rodriguez-Castillo 2003). Nitrate concentration can be used to validate a groundwater vulnerability assessment. Indeed, 33 wells in the area are sampled in order to observe the nitrate contamination of Hajeb-Jelma groundwater (Saidi 2006). The analyzed water samples show a high concentration of nitrate in the Northern east and Southern west part and correspond to both high intrinsic vulnerability and very high risk to contamination. Results are presented in (Fig. 30, ESM) and concentrations (expressed as NO3-) range from 0 to 70 mg/l with a relatively high variability between wells. Results and discussion DRASTIC map shows three classes of vulnerability: medium, high and very high (Fig. 5). The risk map shows a very high risk of groundwater to contamination where human activities are concentrated. In the rest of the aquifer the absence of anthropogenic activities, placed in high and moderate vulnerability zones, implicate a high and medium risk (Fig. 6, ESM). These vulnerability and risk classes are too relative: a site with moderate vulnerability or risk does not mean that

Environ Earth Sci (2010) 59:1579–1588

is free from groundwater contamination, but is relatively less susceptible to contamination compared to the others. The application of the DRASTIC approach reveals some advantages, but also shows some drawbacks. Indeed, the outputs of DRASTIC index depend strongly on the available information (from different sources and at different mapping scales). This may lead to different assessments for the same case study region. For example, it is difficult to attribute to each lithology the exact value of permeability due to the heterogeneity of the aquifer and the vadose zone media. In addition, DRASTIC index is highly sensitive to the parameter scores, weightings and the numerical values assigned to these parameters are arbitrary. In the development of the vulnerability index, no account was taken of the potentially more rapid groundwater recharge associated with artificial recharge, faults and/or wadis despite the fact that the latter are known to be important local recharge areas. This must be considered a serious weakness in the application of the DRASTIC methodology. A major drawback of vulnerability mapping is the difficulty to validate vulnerability (Andreo et al. 2005). In fact, the vulnerability estimation should include contamination potential size and age of infrastructural installations. Groundwater indicators applied to Hajeb-Jelma demonstrate that vulnerability is the differential exposure to stresses experienced by different exposure units. Finally, a model which predicts the possible evolution of contaminants in the soil groundwater system should be developed in order to quantify human impact on groundwater quality.

Conclusions DRASTIC vulnerability methods do not consider the large variety of specific contaminant types. Indeed, a risk map is used to assess the impact of anthropogenic activities on Hajeb-Jelma groundwater. The vulnerability map established to Hajeb-Jelma aquifer shows three classes: moderate, high and very high. On the other hand, the risk map demonstrates high and very high risk zones. These two maps are seen as a promising tool for the quantification of the agricultural practice impact on groundwater quality. While, these maps could be used as a general guide to vulnerability and risk, local conditions on the water resources must be taken into account by local managers and planners. The integration of all indicators: environmental (vulnerability), economic (groundwater extraction and agricultural purposes) and social (groundwater accessibility and use) implicates a crucial state of groundwater resources. Hence, it is necessary for managers to appreciate the

1587

efficacity of hydrogeologic and vulnerability investigations to preserve water resources.

References Adamat R, Foster I, Baban S (2003) Groundwater vulnerability and risk mapping for the Basaltic aquifer of the Azraq basin of Jordan using GIS, remote sensing and DRASTIC. J Appl Geography 23:303–324 Aller L, Bennet T, Lehr JH, Petty RJ, Hackett G DRASTIC (1987) A standardised system for evaluating groundwater pollution potential using hydrogeologic settings. US Environment Protection Agency Report (EPA/600/2-87/035), Robert S; Kerr Environmental Research Laboratory, pp 455 Andreo B, Goldscheider N, Vadillo I, Maria Vias J, Neukum C, Sinreich M, Jime´nez P, Brechenmacher J, Carrasco F, Hotzl H, Jesus Perles M, Zwahlen F (2005) Karst groundwater protection: first application of a Pan-European Approach to vulnerability, hazard and risk mapping in the Sierra de Libar (Southern Spain). J Sci Total Env 357:54–73 District of the Water Resources (DWR) of Sidi Bouzid (2004) Annuaires de surveillance de pie´zome´trie et de salinite´ District of the Water Resources (DWR) of Sidi Bouzid (2005) Comptes rendus des forages et pie´zome`tres de surveillance El Ghali A (1992) Evolution tectono-se´dimentaire du bassin de Jebel Trozza au cours du Cre´tace´ moyen et supe´rieur. Notes du service ge´ologique de Tunisie, pp 59–75 Ferreira JP, Oliveira M (1997) DRASTIC groundwater vulnerability mapping of Portugal. Groundwater: an endangered resource. In: Proceedings of theme C of the 27th Congress of the International Association for Hydraulic Research, San Francisco, pp 6 Institut de la Me´te´orologie Nationale (INM) (1974–2005) Tableaux climatologiques mensuels, stations Sidi Bouzid et Kairouan Koschel R (1980) Etude hydroge´ologique de la nappe de Hajeb el Ayoun-Jelma-Ouled Asker. Division des ressources en eau de Tunis, pp 117 Lobo Ferreira JP, Cabral, M (1991) Proposal for an operational definition of vulnerability for the European Community’s Atlas of groundwater resources, in the framework of the meeting of the ‘‘European Institute for water, Groundwater Work Group Brussels’’ Margat J (1968) Vulne´rabilite´ des nappes d’eau souterraine a` la pollution (groundwater vulnerability to contamination). Bases de la cartographie, (Doc) BRGM, 68SGL198 HYD, Orleans France Michaud Y, Lefebvre R, Martel R (2003) Vulne´rabilite´: Introduction et me´thodologie. Centre Ge´oscientifique de Que´bec, pp 9 Moon SK, Woo NC, Lee KS (2004) Statistical analysis of hydrographs and water-table fluctuation to estimate groundwater recharge. J Hydrol 292:198–209 RAAD (2005) Annuaire d’exploitation des nappes phre´atiques du gouvernorat de Sidi Bouzid. Rapport ine´dit RAAD of Sidi Bouzid (2004) Carte agricole de Sidi Bouzid. Rapport ine´dit Ramos-Leal JA, Rodriguez-Castillo R (2003) Aquifer vulnerability mapping in the Turbio river valley, Mexico: a validation study: Geofisica Internacional 42(1), pp141-156 Saidi S (2006) Etude de la vulne´rabilite´ des ressources hydriques du bassin Hajeb-Jelma (Tunisie Centrale). Me´moire de Maste`re de l’Universite´ de Sfax, pp 121 Secunda S, Collin M, Melloul AJ (1998) Groundwater vulnerability assessment using a composite model combining DRASTIC with extensive land use in Israel’s Sharon region. J Environ Manage 54:39–57

123

1588 SONEDE (2005) Exploitation des forages destine´s pour l’alimentation en eau potable de la nappe Hajeb-Jelma. Rapport ine´dit Sophocleous MA (1991) Combining the soil water balance and waterlevel fluctuation methods to estimate natural groundwater recharge: practical aspects. J Hydrol 124:229–241 Vrba J, Zaporozec A (1994) Guidebook on mapping groundwater vulnerability. International Association of Hydrogeologists, vol 16. International Contributions to Hydrogeology, Heise Hannover, pp131

123

Environ Earth Sci (2010) 59:1579–1588 Zaporozec A (2002) Groundwater contamination inventory, UNESCO Technical Documents in Hydrogeology. Contributions to IHP-V, Project 3.1 Zouari K (1998) Etude isotopique et hydrochimique des syste`mes multicouches de Gafsa et de Hajeb el Ayoun-Jelma. Rapport final de coope´ration scientifique et technique. Projet AIEA. Code: TUN/8/012, pp 70