Arab J Sci Eng (2012) 37:1405–1421 DOI 10.1007/s13369-012-0261-y
R E S E A R C H A RT I C L E - E A RT H S C I E N C E S
Fatma Ben Brahim · Hafedh Khanfir · Salem Bouri
Groundwater Vulnerability and Risk Mapping of the Northern Sfax Aquifer, Tunisia
Received: 3 February 2011 / Accepted: 4 September 2011 / Published online: 21 April 2012 © King Fahd University of Petroleum and Minerals 2012
Abstract In recent years, the groundwater resources of coastal regions of Tunisia (Northern-Sfax) are undergoing significant exploitation and deterioration by chemical fertilizers causing an enormous degradation of their quality. In this study, DRASTIC model is integrated with the Geographical Information System (GIS), in order to assess aquifer vulnerability characteristics and risk maps. Indeed, GIS provide tools to reclassify vulnerability maps to depict areas of high, medium and low vulnerability based on some pre-specified criteria. The vulnerability map of Northern Sfax groundwater exhibits greater variability along the coast than interior section of the area. The risk map shows three classes low, moderate and high risk depending on the hydrogeological properties, land use and human impacts in major part of this study area. This approach should prove useful to regional planners and environmental managers entrusted with the protection of groundwater resources. Keywords Groundwater · Vulnerability · DRASTIC model · Parameter · Risk map · Northern-Sfax
1 Introduction Irrigation and fertilization have caused substantial changes in the hydrology and chemistry of groundwater in agricultural areas. These effects depend locally on many variables including the source of irrigation water (groundwater, surface water, and recycled wastewater), the configuration of the irrigation water distribution system (e.g., canals, furrows, and sprinklers), the fertilizers and other additives used (e.g., nitrogen, lime, and potash), and the hydrogeologic setting (e.g., soil permeability, depth to the water table, and relative aridity) [1]. Excess infiltration of irrigation water can introduce agricultural contaminants to underlying groundwater and rising water levels can result in soil Salinization. High rates of infiltration recharge can alter groundwater flow F. Ben Brahim (B) · H. Khanfir · S. Bouri Water, Energy and Environment Laboratory (LR3E), National School of the Engineers, B.p.w. 3038, Sfax, Tunisia E-mail:
[email protected]
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systems and may result in shorter groundwater residence times and less time for biogeochemical reactions such as respiration, denitrification or mineral dissolution in aquifers beneath irrigated land. These effects cannot all be predicted in every situation; therefore, improved analytical tools are needed for evaluating irrigation effects on groundwater to permit better optimization of fertilization and water use in a variety of agricultural settings. The purpose of this study is to incorporate the Geographical Information System (GIS) to generate groundwater vulnerability and risk maps with DRASTIC model. DRASTIC is an index model designed to produce vulnerability scores for different locations by combining several thematic layers. It was originally developed for manual overlay of semi quantitative data layers, however, the simple definition of its vulnerability index as a linear combination of factors shows the feasibility of the computation using GIS [2]. GIS is designed to collect diverse spatial data to represent spatially variable phenomena by applying a series of overlay analysis of data layers that are in spatial register [3]. The maps of aquifer vulnerability to pollution are becoming more and more in demand because, on the one hand groundwater represents the main source of drinking water, and on the other hand high concentrations of human and economic activities, e.g., industrial and agricultural represent real or potential sources of groundwater contamination [4]. The definition of the term vulnerability is not ambiguous. First of all, vulnerability is often defined merely with regards to water quality, though it may include aspects of water quantity. According to Vrba and Zaporozec [5] who quoted the earliest definitions found in the literature by Albinet and Margat [6] who stated that aquifer vulnerability is “the possibility of percolation and diffusion of contaminants from the ground surface into natural water table reservoirs under natural conditions”. The objective of this study is to elaborate a synthetic document for the assessment of groundwater vulnerability to contamination in Northern Sfax area using a DRASTIC model combined with a GIS. This model has been widely used in many countries because the inputs required for its application are generally available or easy to obtain. It is based on seven parameters to be determined as input by computing the DRASTIC index number, which reflects the pollution potential for the aquifer [7]. 2 Description of the Study Area This study concerns three regions (El Hancha, Djebeniana and El Amra) of the Northern Sfax area, located at the central East of Tunisia (Fig. 1). These regions have an arid to semi arid Mediterranean climate with large temperature and rainfall variations. Average annual temperature and rainfall are about 19 ◦ C and 225 mm, respectively [8]. Increase of the agricultural irrigation return, domestic effluents and intensive pumping have largely contributed to contamination of groundwater. The geology of the studied area is investigated by several authors [9–14]. The Mio-Plio-Quaternary and the Quaternary terrains occupy a large part of the study area; they are considered by actual and recent alluvial deposit: conglomerates, gravels, silts, calcareous, etc.
Algeria
Tunis
Sebkha el Jem
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Study Area
Sfax Gabes
Libya
El Hancha 0
80Km
El Amra
ME DI TE RR
AN
EA N
SE A
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Locality 0
Fig. 1 Localization of the study area
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Fig. 2 Geologic map of the Sahel of Sfax showing the study area
The aquifer is recharged by direct infiltration and its higher limit is at Medasse Sidi salah, the discharge limits coincide with the Mediterranean shore line and the sebkha of el Jem (Fig. 2). The groundwater flow is generally toward the South-east, implying discharge to the Mediterranean Sea, the natural outlet and may be locally disturbed by the piezometric depressions due to the intensive exploitation in this study area. The pumping well density was about 4,578 wells in 2006, whereas it was of 3,570 wells in 2001 [15]. The synthetic geological cross section along the three regions presented in Fig. 3 shows the presence of a horizontal structure composed of a slightly clayey sand level of Mio-Plio-Quaternary age. This latter is limited to the bottom by a clay layer, representing the aquifer substratum. On the top, heterogeneous clastic materials presented essentially by sand and gravel are encountered, implying a generally permeable aquifer. 3 Materials and Methods This survey is based on multi-database obtained from multi-sources [15–17]. 3.1 DRASTIC-Based Vulnerability Mapping A DRASTIC model and a GIS were used to evaluate the vulnerability of the Northern Sfax aquifer. This involves: (1) collective hydrogeological and geological data, (2) standardizing and digitizing source data,
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Nozha
Nozha Zelba Est
Zelba Est
Blettech Saint Louis
Kcherma
Mhara Sud
Draa Ben Zied
Bderna
4 Km
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10m Blettech
20m 30m
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SE
Kcherma
piezometer Cross-section Locality
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60m
Legend
Gravel Clay Marl Sandy-clayey Clay well name
Fig. 3 Synthetic geological cross section along the three regions Table 1 Weights assigned for DRASTIC factors Factor
Meaning
Assigned weights
D R A S T I C
Depth to water Net recharge Aquifer media Soil type Topography Impact of the vadose zone media Conductivity
5 4 3 2 1 2 3
(3) constructing an environmental database, (4) analyzing the DRASTIC factors, (5) calculating the DRASTIC index for the hydrogeological settings, and (6) rating these areas as to their vulnerability to contamination. The DRASTIC methodology (model) was originally 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 [7,18]. The acronym DRASTIC stands for the seven hydrogeological parameters which are: depth to groundwater (D), net recharge by rainfall (R), aquifer media (A), soil media (S), topography (T ), impact of vadose zone media (I ) and the hydraulic conductivity of the aquifer (C). The model yields a numerical index that is derived from ratings and weights assigned to the seven model parameters. The significant media types or classes of each parameter represent the ranges, which are rated from 1 to 10 based on their relative effect on the aquifer vulnerability. The seven parameters are then assigned weights ranging from 1 to 5 reflecting their relative importance with respect to each other. The DRASTIC index is then computed applying a linear combination of all factors according to the following equation: DRASTIC index = Dr Dw + Rr Rw + Ar Aw + Sr Sw + Tr Tw + Ir Iw + Cr Cw where D, R, A, S, T, I, and C are the seven parameters and the subscripts r and w are the corresponding ratings and weights, respectively. This model was selected based on the following considerations. DRASTIC uses a relatively large number of parameters (seven parameters) to compute the vulnerability index, which ensures the best representation of the hydrogeological setting. The numerical ratings and weights, which were established using the Delphi technique [7], are well defined and are used worldwide (Table 1). This makes the model suitable for producing comparable vulnerability maps on a regional scale. All maps were reclassified using rating factors presented in Tables 3, 4, 5, 6, 7, 8 and 10. The necessary information needed to build up the several model parameters was available in the study area or could easily be inferred. The final DRASTIC vulnerability map was reclassified into three vulnerability states namely: high, medium and low. The most important assumptions made when assessing vulnerability with DRASTIC [7] are that the contamination is introduced at the ground surface flushed into the groundwater by precipitation and has the mobility of water. This method takes 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, Arc Map and Arc Info. 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
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Table 2 Data sources used for constructing the DRASTIC parameters DRASTIC parameters
Type of data
Depth to groundwater (D) Rainfall distribution (R)
Static level statement of the years 2005–2006–2007 [16,17] Annual rainfall data during the period 1995–2005 (INM, 2005) Aquifer media (A) Equivalent permeability taken from well logs (DWR) Soil type (S) Soil map (Agricultural maps obtained from the Regional Agency of Agricultural Development “CRDA” of Sfax 2007) Topography (T) Topographic maps with the 1/50,000: sheets N◦81,82, 89,90,97 and 98 (CRDA, 2006) Impact of vadose zone (I) Equivalent permeability taken from well logs (DWR) Hydraulic conductivity (C) Permeability calculated from the transmissivities Taken from the pumping tests (DWR)
Format
Mode of processing data
Table Table
Interpolation Interpolation
Table Map
Interpolation Digitalization
Map sheet
Digitalization
Table Interpolation Table and Map Interpolation
Table 3 Rating and weight of the depth to groundwater parameter [7] Factor: depth to groundwater (D) Depth to groundwater (m) 4.5–9 9–15 15–23 23–31 31–83 Weight = 5
Rating 7 5 3 2 1
Table 4 Rating and weight of the net recharge parameter [7] Factor: net recharge (R) Net recharge (m) 166–170 170–225 225–247 Weight = 4
Rating 6 8 9
Table 5 Rating and weight of the Aquifer media parameter [7] Factor: aquifer media (A) Permeability classes (m) Sand and clay (5 × 10−5 to 2 × 10−4 ) Massive clay and sand (2 × 10−4 to 4 × 10−4 ) Sand, gravel and clay (4 × 10−4 to 5 × 10−4 ) Sand and gravel (5 × 10−4 to 10−3 ) 10−3 to 10−2 Weight = 3
Rating 2 4 6 8 10
consists in the fragmentation of a map into a series of pixels whose size is 300×300m. 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 are also used to elaborate the groundwater vulnerability map by overlaying the seven thematic maps. 3.2 Preparation of the Parameter Maps Several types of data were used to construct thematic layers of the seven model parameters. A summary of the data types, sources and usages is available in Table 2. The location of the 17 monitoring wells in Northern Sfax
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Table 6 Rating and weight of the soil media parameter [7] Factor: soil media (S) Soil types
Rating
Built-up areas Halomorphic soil Gypsum soil Polygene-tic soil Soil with little evolution Calcareous brown soil Rendzina Isohumic (chestnut) soil Mineral soil Weight = 2
1 2 3 4 5 6 7 8 9
Table 7 Rating and weight of the topography parameter [7] Factor: topography (T) Slope (%)
Rating
0–3 3–5 5–10 5–15 Weight = 1
10 9 5 3
Table 8 Rating and weight of the impact of the vadose zone parameter [7] Factor: vadose zone media (I) Permeability classes (m) Clay and sand and calcareous (0.5 × 10−4 to 2 × 10−4 ) Sand, silt and gravel (2 × 10−4 to 4 × 10−4 ) 4 × 10−4 to 5 × 10−4 5 × 10−4 to 10−3 10−3 to 10−2 Weight = 5
Rating 2 4 6 8 10
aquifer was digitized from the accompanying topographic map and was linked to an attribute table containing the depth to groundwater table. Essentially, the elevation of the well and the mean groundwater level were provided for the three years (2005–2007). The depth to water was obtained by subtracting the groundwater level from the elevation of the well. In a relatively small area and a fairly isotropic aquifer, the static water level exhibits a smooth and gradual change of heads. Therefore, an exact interpolation scheme is appropriate for generating a smooth surface representation for the high degree of spatial continuity of the depth to groundwater parameter in an aquifer. The inverse distance moving average interpolation method was therefore performed on the point data. The weight of an input point is proportional to its distance from the output pixel. The inverse distance is the weight function which ensures that relatively larger weights are assigned to points close to an output pixel. This better satisfies the interpolation scheme and helps generate the smooth surface representation suitable for such type of data. The recharge map was constructed from the rainfall data according to the following formula: Net recharge = (rainfall − evapotranspiration) × recharge rate The rainfall map was obtained by interpolating a 10-year mean of annual precipitation (mm/year) from six representative rainfall stations in the Northern Sfax area. The inverse distance moving average interpolation technique described above was used to construct the rainfall map. The aquifer media and the impact of vadose zone maps were obtained by interpolation using the database of well logs provided by the District of the Water Resources of Sfax during the period 2005–2007.
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Fig. 4 Depth to groundwater map (2007)
The soil map was imported from the agricultural map in digital format into the Arc-View GIS program, referenced to area coordinates and on-screen digitized to delineate the different soil units. The topography layer was also constructed from the topography map by digitalization. The topography was first scanned and registered. The elevation contour lines were digitized together with the elevation points to be used in the interpolation. The hydraulic conductivity map was also scanned and spatially registered. The different hydraulic conductivity zones in the area were defined and assigned ratings according to DRASTIC. 3.3 Combining Database for the DRASTIC Vulnerability Index For the application of DRASTIC model to the aquifer of Northern Sfax, a multidisciplinary data bank is highly needed 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 previous geological studies [9,12], hydrogeological studies [15,19], a climatologic study [8], and soil studies [20]. 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 January 2006 in order to measure piezometric level and collect groundwater samples [16] to update the old data. 3.4 Modification of the DRASTIC Method For the assessment of pollution potential in this survey, 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 soil classes cannot be found in the table of Aller et al. [7] classification and a wide 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 (Tables 5 and 8). 3.5 Development of the DRASTIC Vulnerability Index 3.5.1 Depth to Groundwater (D) Depth to water is one of the most important factors because it determines the thickness of material through which infiltrating water must travel before reaching the aquifer-saturated zone. Depth to water consequently impacts on the degree of interaction between the percolating contaminant and sub-surface materials (air, minerals, water) and, therefore, on the degree, extent, physical and chemical attenuation, and degradation processes. In general, the aquifer potential protection increases with depth to water. Static water level data obtained from 17 monitoring wells, homogenously distributed in the study area were used to provide the depth to groundwater map (Fig. 4).
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Fig. 5 Recharge map
Thus, the depth to groundwater is in the range from 6 to 82 m from the groundwater surface. The depth index is obtained as a result of multiplying Dr × Dw based on the weighting of Aller et al. [7] (Table 3; Fig. 4). A low water depth will lead to higher vulnerability rating. Indeed, North, South and Eastern parts of the study area are considered the most vulnerable according to this parameter. 3.5.2 Net Recharge (R) Net natural recharge is defined as the fraction of rainfall that can infiltrate and reach the aquifers. It was determined on the basis of the spatial distribution of rainfall in the study area and the fraction of the evapotranspiration [21]. However, in semi-arid and arid regions where effective precipitation is low, irrigation return flow can be an important component of recharge [22]. Though the source of the recharge values is the water table 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 [23]. In the case of Northern Sfax aquifer (El Hancha, Djebeniana and El Amra), computed annual recharge values varied between 170 and 225 mm. The resulting map of rainfall distribution is established by interpolation. Then it is classified and multiplied by the weighting factor of the recharge parameter as shown in Table 4 and Fig. 5. The amount of recharge is positively correlated with the vulnerability rating. 3.5.3 Aquifer Media (A) Aquifer refers to the portion of ground capable of yielding water in pores. The contaminant attenuation of aquifer depends on the amount and sorting of fine grains. In general, the larger the grain size and the more fractures or openings within the aquifers, the higher the permeability and the lower the attenuation capacity, consequently, the greater the pollution potential [24]. Information needed to evaluate this critical factor was obtained from the equivalent permeability which is found in the well log reports [15]. The aquifer media map of this study area shows that the horizontal equivalent permeability values are between 4 × 10−6 and 68 × 10−4 (m/s). It has rating between 1 and 10 affected by a weight of 3 (Table 5; Fig. 6). 3.5.4 Soil Media (S) The soil media found in the study area is generally variable (Table 6). The different soil types were assigned rates according to their permeability (depending on the texture). A high score (9) was assigned to the mineral soil and the lowest score (1) was assigned to the soil in the built-up areas. The gypsum soil and calcareous brown soil were assigned moderate rating scores (3–6). The selected soil media and corresponding ratings are mapped in Fig. 7a. The vector layer of soil is converted to raster grid and multiplied by the weighting factor of the soil media (2) which has produced the map of Sr × Sw as shown in Fig. 7b.
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Fig. 6 Permeability of the aquifer media map
Fig. 7 a Soil media map. b Soil media grid map
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Fig. 8 Map depicting slopes
Fig. 9 Permeability of the vadose zone map
3.5.5 Topography (T) Topography, which in this case refers to the percent slope of the land surface, was determined directly from the fort topographic maps (scale 1:50,000) covering the study area of Northern Sfax. The (average) percent slope is obtained within 3D analyst function of Arc View GIS. After mapping the percent slope values, the value of the slope index is reclassified and converted into grid coverage and multiplied by topographic weight as shown in Fig. 8. The Topography layer displayed a gentle slope (0–15 %) over most of the study area which has been assigned the DRASTIC rating scores of 3 and 10. The slope percentage increases southwest of the study area. These areas with steep slopes (15 %) were typically assigned a low rating score (3) indicating their minimal effect on the aquifer vulnerability. Fort slope classes are extracted (Table 7) and for each a rating value is attributed. It has a rating between 3 and 10 and the major percent slope is 9 indicating their maximal effect on the aquifer vulnerability. 3.5.6 Impact of the Vadose Zone Media (I) This parameter is represented by the equivalent permeability which is found in well logs from DWR [15]. Vertical equivalent permeability values are between 5.10−5 and 10−2 m/s. It has rating between 2 and 10 and affected by a weight of 5 (Table 8; Fig. 9).
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0
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DRASTIC index 80-99 100-119 120-139 140-159 160-181 No data
Fig. 10 Intrinsic vulnerability index mapping Table 9 Criteria for evaluation of vulnerability in the DRASTIC method [7] Vulnerability degree
Vulnerability index (I)
Very low Low Moderate High Very high
I < 80 80–120 120–160 160–185 I > 185
3.5.7 Hydraulic Conductivity (C) This parameter is defined as the ability of aquifer materials to transmit water, which in turn, controls the rate at which groundwater will flow under a given hydraulic gradient. The rate, at which the groundwater flows, also controls the rate at which it enters the aquifer. The hydraulic Conductivity of the Northern Sfax 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 (m). The hydraulic conductivity map (Fig not shown), obtained by interpolation, is converted to a raster grid and multiplied by the weighting factor (3). The latter has produced the map of Cr × Cw . 3.5.8 The DRASTIC Vulnerability Index According to the range of Aller et al. [7], the DRASTIC vulnerability index was determined by overlying the seven thematic layers. All the GIS data coverage is in raster format and values for each overlay are summed in Arc View GIS according to pixel value of each area that resulted from multiplying the ratings with appropriate DRASTIC weight. The resulting DRASTIC values lay between 80 and 181 (Fig. 10). This range is classified on the basis of the above classification as: (1) 88–119, which is assigned a low vulnerability, (2) 120–159, is represented by a moderate vulnerability and (3) 160–181, which is assigned a high vulnerability (Table 9). The Digital Terrain Model, including 3D analyst extension of Arc GIS was used to generate a good visualization of the different vulnerability classes (Fig. 11). 3.5.9 Validation of the Intrinsic Vulnerability Maps Aquifer vulnerability method requires validation to reduce subjectivity in the selection of rating and to increase reliability [25]. The spatial distribution of nitrate concentration can be used to validate a groundwater
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Vulnerability index Low vulnerability (80-119) Moderate vulnerability (120-159) High vulnerability (160-181) No data
Fig. 11 Intrinsic vulnerability mapping
El Hancha
Study area boundary
SE A
AN EA N
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NO3 (mg/l) 9.1 - 26.2
TE RR
El Amra
77.5 - 111.7
M ED I
7
26.2 - 43.3 43.3 - 60.4 60.4 - 77.5
0 Km
Fig. 12 NO3 concentration map in Northern Sfax aquifer
vulnerability assessment. Indeed, 43 wells in the area are sampled in order to observe the nitrate contamination of Northern Sfax groundwater [16]. Results are presented in Fig. 12 and concentrations (expressed as NO− 3) range from 0 to 111.7 mg/l with relatively high variability between wells. The distribution of nitrate shows a high concentration in the majority of the study area which are greater than the recommended limit 45 mg l−1 proposed by the World Health Organization [26] and also reveals the same tendency reflected in the intrinsic vulnerability index mapping (see Fig. 10). The DRASTIC model seems to be suitable to demonstrate that the water resources are threatened by the artificial fertilizers (nitrates). The absence of sanitation network in the whole region contributes to the nitrification of ground waters according to the process. In addition, the salinity map of the aquifer shows an increasing tendency along the coastal zones (Fig. 13a). This might be explained by the intensive pumping which tends to be quite important zones of low piezometric levels (Fig. 13b, c). 3.5.10 Development of the DRASTIC Risk Assessment Vulnerability is distinct from pollution risk which depends not only on hydrogeological conditions but also on the existence of significant pollutant loading entering the subsurface environment [27,28]. 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. The use of the vulnerability map can be relevant only if the human activities data have an impact on the quality and the quantity of the water resources. In order to evaluate the risk pollution, we could integrate and overlay the map of the anthropogenic activities (agriculture, industry, urban development) with the vulnerability map. In fact, The Northern Sfax area shows a variety of potentially polluting activities, which are dynamic factors that can be changed and controlled.
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Fig. 13 a Distribution of salinity in the aquifer system in the study area. b Localization of pumping well in the study area (2007). c Piezometric map of the aquifer system in Northern Sfax region (2007)
3.5.11 Risk Map Using Land Use Map and DRASTIC Vulnerability Map For evaluating potential risk, an additional parameter could be integrated, which is the land use (Fig. 14). In order to introduce a land use factor into the DRASTIC index, the land use map is rated according to the Secunda et al. [29] (Table 10). This map is converted into a raster gird and is multiplied by the weight of the parameter (Lw = 5). The resultant gird coverage is then added to the DRASTIC index based on the Equation [29]: MD(i) = DI+Lr ×Lw . Where DI is the DRASTIC index and Lr × Lw is the land use index, the modified DRASTIC index is sub-divided into fort classes (Fig. 15). Indeed, the urban zones are characterized by a high risk whereas the public and private irrigated areas present a very high risk.
3.5.12 Risk Map Using Hazard Map and DRASTIC Vulnerability Map In this method, risk assessment includes all activities that consider the possible origins of pollution. The points of potential contamination release are determined with hazard assessment where all possible origins of pollution and likelihood of its release are considered [30]. In order to attain the risk assessment, we could overlay the hazard map (Fig. 16) and the vulnerability map (Fig. 11).
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Built Up Areas Irrigated field crops Uncultivated Areas
Fig. 14 The major land use classes in the study area Table 10 Land use categories for the study area and the weight of this parameter [29] Land use category
Lr
Built up area Irrigated field crops Uncultivated land Lw
8 8 5 5
Djebeniana
0
5Km
Modified groundwater vulnerability Low Moderate High Very high
Fig. 15 The modified groundwater vulnerability + risk index
Despite differences between the two risk maps (Figs. 15, 17), both methods show a high risk of groundwater to contamination where human activities are concentrated. In the rest of the aquifer, the absence of anthropogenic activities, placed in low and moderate vulnerability zones, implicate a high and medium risk. These vulnerability and risk classes are too relative: a site with moderate vulnerability or risk does not mean that it is free from groundwater contamination, but is relatively less susceptible to contamination compared to the others. The observation of these maps shows that the best correspondence is observed where there is a high density of wells (high density of information). Thus to obtain a better validation, another monitoring wells should be analyzed, to cover the area with few data.
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Domestic effluents Industrial discharge Roads
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Fig. 16 Hazard map of the study area
Risk classes
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Fig. 17 The risk map made by overlaying the vulnerability and the hazard maps
4 Conclusions The assessment and classification of aquifer vulnerability in Northern Sfax region is often carried out to guide land use and water resources planning endeavors. The use of DRASTIC approach with GIS for visualizing aquifer vulnerability characteristics has become a standard practice with the easy availability of the required data in digital format. The present study is based on the premise that the utility of digital vulnerability mapping is further enhanced when the generated data is effectively mined for insights and information. The DRASTIC vulnerability methods were adapted in this study to understand regional scale aquifer vulnerability in Northern Sfax according to the perceived risks to groundwater resources based on hydrogeologic characteristics. Thus, the vulnerability map established in this study area shows three classes: low, moderate and high. On the other hand, the risk map demonstrates moderate, high and very high risks zones where the anthropogenic sources are concentrated. In Northern-Sfax region, the groundwater is thus threatened not only by the massive usage of artificial fertilizers, but the domestic effluents, industrial discharges and intensive pumping are also sources of contamination. These elaborated maps are seen as promising tools 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.
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Acknowledgments The authors are grateful to all those who provided us with the necessary data to accomplish our study. Especially, we thank the engineers of the District of the Water Resources (DWR) of Sfax and the reviewers for their comments.
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