INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCES Volume 7, No 2, Copyright by the authors - Licensee IPA- Under Creative Commons license 3.

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1 INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCES Volume 7, No 2, 2016 Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0 Research article ISSN Assessment of groundwater vulnerability zones using GIS-based DRASTIC Model: A case of Makutupora Basin, Mary J. Kisaka 1, Meserecordias W. Lema 2 1- Assistant Lecturer, College of Earth Sciences, University of Dodoma, P.O Box 259, Dodoma, Tanzania 2- Lecturer, College of Earth Sciences, University of Dodoma, P.O Box 259, Dodoma, Tanzania drlemaofficial@gmail.com doi: /ijes.7013 ABSTRACT This study was conducted in the Makutupora basin to evaluate the vulnerability of groundwater to contamination using DRASTIC method in a GIS (Geographical Information System) environment. ILWIS 3.0 (Integrated Land and Water Information System) and Arc view 3.2a GIS software were also used to find water vulnerable zones in the aquifers. Estimation of DRASTIC Index involves multiplying each parameter weight by its rating corresponding to its study area and summing the total. A groundwater pollution potential map was prepared and the DRASTIC Index (DI) of the area was calculated. The values for the DRASTIC index were classified into five classes: extremely low, low, moderate, high and extremely high. From this study, it was found that about 30 % of the study area is occupied by high to extreme vulnerability, 20 % is occupied by moderate vulnerability and 50 % is occupied by the low to extremely low vulnerability. Areas with high to extreme vulnerability were due to fractures associated with aquifer, high recharge potential, shallow water table as well as agriculture activities. The vulnerability map produced could be useful for planners and decision makers for initiating groundwater quality development in their specific areas. Keywords: DRASTIC, GIS, vulnerability, groundwater, aquifer. 1. Introduction Water is considered to be the basic element for a healthy society. It is also responsible for a sustainable economic development (Murali and Elangovan, 2013). Groundwater is one of the valuable earth s non-renewable resources for human life and economic development, which occur as a part of hydrological cycle. It is found as major source of water for domestic, agricultural and industrial purposes in many countries (Ramesh and Elango, 2011). It is estimated that 2 billion people worldwide rely on groundwater for drinking water supply. This is due to its relatively low susceptibility to pollution compare to surface water (Arzu and Gültekin, 2013). Environmental concerns related to groundwater generally focus on the impact of pollution and quality degradation in relation to human consumption. In most areas, groundwater pollution is related to high population growth, industrialization, unplanned growth of urban areas and lack of proper sewage systems. Furthermore, the application of fertilizers and pesticides during agricultural activities is usually a subject to groundwater quality contamination (Arzu and Gultekin, 2013) A study by United States of America s National Research Council (1993) showed that groundwater is vulnerable to pollution, and once polluted, it is very difficult to remediate. Therefore, a sustainable groundwater management should rely on prevention of Received on January 2016 Published on September

2 contamination. Groundwater vulnerability measures on how easy or hard it is for pollution or contamination at the land surface to reach a production aquifer (Thomas and Leah, 2001). It tends to combine the hydraulic inaccessibility of the saturated zone to the penetration of pollutants, with the attenuation capacity of the strata overlaying the saturated zone to the penetration of pollutants, with the attenuation capacity of the strata overlying the saturated zone as a result of physical chemical retention or reaction of pollutants (Foster, 2007). It is designed to help planners to protect aquifer as an economic resource (Robins et al., 2004). Although groundwater quality in Tanzania is considered potentially good and acceptable for most use it still faces challenges of salinity, high fluoride, hardness, corrosion, nitrate (Mato and Mujwahuzi, 2010). Makutupora aquifer which is located about 35 km from Dodoma town is used as a major source of portable water. Makutupora. Much work has been done in this aquifer to determine water quality and quantity. So far no study has been undertaken to assess vulnerability of groundwater using DRASTIC model (DM) and GIS (Geographical Information System) approach. To ensure this aquifer remains as a potential source of clean and safe water for the Dodoma municipality, it is necessary to carry out a study to establish potential areas in this groundwater basin that are susceptible to water pollution. Therefore, this study aims at using DM to assess groundwater vulnerability of the Makutupora basin, to pollution. 2. Material and methods 2.1 Study area Makutupora basin (Figure 1) is found in Dodoma region and lies in the Gregory rift system. It is located between latitudes; and S and longitudes; and E (Rwebugisa, 2008). The Makutupora well field covers an area of 6000 hectares with a catchment area of 34,000 hectares. (Ngana et al., 2010). The principal soil types are white sandy soil, read loam soil and black clay soil (Shindo, 1991). The white sand soil is the most dominant and covers an extensive area of pedplain uplands and mountain slopes. It is composed of granite rocks with high infiltration capacity and is considered to be the area of ground water recharge. The region has an average annual rainfall of 550mm with a single rain season, mostly from November to April (Shindo, 1991; Rwebugisa, 2008). A study by Shindo (1990) showed that distribution of rainfall in the study area tends to vary locally, whereby, there is higher amount of rainfall in the mountainous side and relatively low rainfall in the western part which is a lowland The monthly maximum temperature is 26 c which occurs around February, while monthly minimum is 21 c which falls around July, each year (Rwebugisa, 2008). The topography of the study area is dominated by inselbergs and pediment plain, underlain by Precambrian basement rocks and basin floor (Rwebugisa, 2008). 2.2 DRASTIC model The DRASTIC model was developed in USA for the purpose of protecting the groundwater resources (Aller et al., 1985). DRASTIC is an empirical groundwater model that estimates groundwater contamination vulnerability of aquifer systems based on the hydrogeological settings of that area. The DRASTIC hydrogeological vulnerability ranking method uses a set of seven hydrogeological parameters to classify the vulnerability or pollution potential of an aquifer. The parameters are: 133

3 1 Depth of groundwater (D); 2 Recharge rate (R); 3 Aquifer media (A) 4 Soil media (S); 5 Topography (T); 6 Impact of the vadose zone (I); and 7 Hydraulic Conductivity of the aquifer (C) Figure 1: Makutupora Basin location map However, each parameter is assigned a relative weight from one to five based on its relative susceptibility to a pollutant as shown in Table 1 (Aller et al., 1985). Similarly, parameter rankings are assigned on a scale of one to ten (1-10) and are based on its significance to pollution potential in an assessed area. The set of variables that are considered for the DRASTIC model can be grouped according to three main categories: land surface factors, unsaturated zone factors and aquifer or saturated zone factors. The aquifer media properties and the hydraulic conductivity are the critical factors identified for the saturated zone. The depth to water and the properties of the vadose zone characterize the water/contaminant path down to the saturated zone. In soil and the unsaturated zone, some mechanisms may affect the contaminant concentration much more than in the saturated zone (Gogu et al., 2000). Table 1: DRASTIC Parameters assigned weights Factor Weight D Depth to water 5 R Net Recharge 4 A Aquifer Media 3 S Soil Media 2 T Topography 1 I Impact of Vadose Zone 5 C Hydraulic Conductivity of the Aquifer 3 (Source: Aller et al., 1985) The DRASTIC Index was computed by summing the weighted factors of each subdivision of the area. Generally, higher DI value indicates greater susceptibility to groundwater pollution. 134

4 Where: Dr = Ratings to the depth to water table Dw = Weights assigned to the depth to water table. Rr = Ratings for ranges of aquifer recharge Rw = Weights for the aquifer recharge Ar = Ratings assigned to aquifer media Aw = Weights assigned to aquifer media Sr = Ratings for the soil media Sw = Weights for soil media Tr = Ratings for topography (slope) Tw = Weights assigned to topography Ir = Ratings assigned to vadose zone Iw = Weights assigned to vadose zone Cr = Ratings for rates of hydraulic conductivity Cw = Weights given to hydraulic conductivity 1.1 Each parameter is assigned the same weight all over the area but different ratings, according to the hydrogeological and geological conditions in the area. Using the above equation with the aid of a GIS, DRASTIC index values were obtained. According to the ranges, the degree of vulnerability of each area was determined; a groundwater vulnerability map was then compiled to show the vulnerability toward contamination of each area. Figure 2: Flow chart of a methodology for ground water vulnerability analysis using DRASTIC model in GIS 135

5 3. Results and discussion 3.1 Development of the DRASTIC parameters Depth to water (D) Depth to water table is a significant parameter of the DRASTIC model controlling the ability of contaminants to reach the groundwater or aquifer. A shallow depth to water table will lead to higher vulnerability rating. The depth to water data was obtained from the Dodoma Regional Water Office (DRWO). Depth to water table in the Makutupora sub basin varies between 9m and 104m which imply that most of the underground water in the study area is deep water. Range values of depth to water are divided into five levels from 0 to 15m to depth of > 75 m. According to DRASTIC model (Aller et al., 1985), the highest rating values were assigned to depth to water levels that are nearer to the surface and more vulnerable to contamination as shown in Table 2 below. Table 2: Range, Rating and Weight for Depth of Water Range (m) Rating Index > DRASTIC Weight = 5 The depth to water table index value (DrDw) ranges from a value of 10 representing the deepest and least vulnerable water level, to 45 where the water table is near the surface. Whereas the greatest percentage of drilled wet boreholes falls within 50 to 75 m range. Figure 3: Depth to water 136

6 In the study area, the greatest depth to water values is predominantly found in Chenene Hills northeast of the Makutupora sub basin and around the borehole 107/72; 77/75 and 97/75. This implies that the contaminants path to the aquifer will be retarded; and potential pollutants released accidentally to the surface cannot reach the aquifer easily Net recharges (R) Net recharge is the total amount of water reaching the land surface that infiltrates into the soil and then continues to percolate through the vadose zone (unsaturated zone) into the groundwater, measured in meters per year. Recharge represents the primary contaminant transport mechanism into the aquifer and depends on the soil characteristics. The prevailing soil in the study area is dark brown sandy clay and black mbuga clay. The primary source of groundwater recharge in the study area is rainfall. Rainfall data is derived from Tanzania Meteorological Agency (TMA) Dodoma station, with 10 years of records ( ), and were used for computing net recharge. Therefore the annual average rainfall of the study area is mm/year (0.6137m/year). The reliability of the estimation of all the components of the groundwater budget largely depends on the accuracy of net recharge (R). There are different techniques available for the estimation of recharge. The chloride mass balance (CMB) was used to evaluate the recharge spatially and temporally. The CMB method is based on the assumption of conservation of mass between the inputs of atmospheric chloride and the chloride flux in the sub-surface (Wood et al., 1999). CMB is a better choice due to its simplicity and less data requirement, but it gives lower recharge values compared to other techniques. The technique is based on the mass balance of chloride and therefore it cannot be applied in areas underlain by evaporates or areas where mixing of saline groundwater occurs and in coastal or industrial areas where high variability of chloride in rainfall occurs. As it was suggested by Rwebugisa (2008), the average chloride content in the rainwater was adopted to be 1.14mg/L. The quantitative net recharge is determined using the following Equation; 1.2 Where R is mean recharge rate in mm, ClP is chloride concentration in precipitation (mg/l), Clgw is chloride concentration in groundwater (mg/l), DCl (mg/l) is dry deposition of chloride (assumed negligible in this study) and P is mean precipitation in mm/yr. The average groundwater net recharge calculated from the analyzed chloride samples through CMB and the distribution in the area is governed by the amount of groundwater flow regime and topography. The higher recharge zone in the southeast part of the study area is due to topography and geomorphology. The recharge values from the CMB method is generally used for steady state numerical models because it represents a long term average recharge estimate due to the slow and complex process of mixing. The rating values were created and were used to compute the recharge index value (RrRw) to show recharge variation over the study area as shown in Table 3. The higher and the lowest recharge values are mostly associated with topography, groundwater flow regime, geomorphology and amount of rainfall. 137

7 Table 3: Range, Rating and Weight for Net recharge Range (mm/yr.) Rating Index > DRASTIC Weight = 4 Higher recharge zones are found in the southeast of the Makutupora sub-basin, while of the study the recharge rates for the remaining part was found to be moderate and low. This implies that when the potential pollutants are accidentally released to the surface, pollutants will spend a long time on the surface before percolating to the aquifer. Meanwhile, areas with high recharge rate has greater potential for groundwater contamination if the pollutants are released onto the surface Aquifer media (A) An aquifer is a body of saturated rock through which water can easily move. The aquifer media has been chosen as the starting parameter because the values chosen for the other parameters depend on this. The aquifer medium determines the materials with which the contaminant is in contact in the aquifer. Hence, it plays a significant role in the concentration attenuation process. Besides, it governs the groundwater flow system and consequently, affects the route and path length that the contaminant follows. The pathways for groundwater flow are strongly influenced by the grain size of the medium, fractures or openings within the aquifer (Babiker et al., 2004). Based on the lithology of the aquifer at each drilled well, the aquiferous rock formations are heterogeneous around the Makutupora sub basin. The aquiferous stratum consists highly weathered/fractured granite which concentrates at the central part of the basin around the pump house, weathered granite with sandy found most at the northern part while sandy clay with gravel is dominated at the rest part of the basin. Using DRASTIC model the aquifer media in the study area was rated as shown in Table 4. Table 4: Range, Rating and Weight for Aquifer media Aquifer media Rating Index Highly granite weathered/fractured 9 27 Weathered granite with sand 7 21 Sand clay with gravel 6 18 DRASTIC Weight = 3 In the study area, the presence of a fracture in the aquifer media implies a higher contamination potential because of the degree of secondary permeability it provides. Also, larger grain size and more fractures or openings imply a higher permeability and thus, a lower pollution attenuation capacity. Similarly, the presence of clay materials in the aquifer lowers the pollution potential. 138

8 3.1.4 Soil media (S) Soil media is the upper and weathered portion of the unsaturated zone. The characteristics of the soil influence the amount of recharge infiltrating into the aquifer, the amount of pollutant dispersion, and the purifying process of contaminants. A number of soil characteristics control the capacity of contaminants movement into the groundwater. Some of these are; thickness of soils which determines the length of time contaminants reside within the media as well as the texture and structure which altogether influence the rate at which water percolates through the soil profile (Babiker et al., 2004). The soil data of the study area was derived from the lithology of each drilled wells and soil report. It was observed that the predominant soil media in the study area is dark brown sandy clay and black mbuga clay. Referring to Thorp and Smith (2008) the soil type in the study area was classified as hydrologic soil group D. According to DRASTIC model the soil media in the study area was rated as shown in the Table 5. Table 5: Range, Rating and Weight for soil media Aquifer media Rating Index Sandy clay soil 3 6 Mbuga clay 2 4 Reddish/Brownish clay soil 1 2 DRASTIC Weight = Topography (T) Topography refers to the slope of the land surface. Topography indicates whether a contaminant will run off or remain on the surface long enough to infiltrate into the groundwater (Aller et al., 1985). Areas with gentle slope tend to retain water for a long period of time. This allows greater infiltration or recharge of water and a greater potential for contaminant migration. To obtain a slope map, a contour map of the study area and Arc GIS 9.3 was used to obtain a percentage slope map. The study area is generally flat with the steep slope at Chenene hills. Using the DRASTIC model (Aller et al., 1985), the flat area was assigned a high rate, because in flat area the run-off is less, so more percolation of contaminants to the groundwater. Other areas were categorized as shown in Table 6. Table 6: Range, Rate and Weight for Topography in the study area Range (%) Rating Index > DRASTIC Weight = 1 Rating corresponding to > 18% slope has a value of 1, and for < 2% slope, a value of 10. The DRASTIC weight assigned for topography is 1. In the study area, at < 2% slope, the greatest potential may exist for contaminant infiltration. At > 18% slope, little potential may exist for infiltration. Generally it is noticed that the area has less potential for contaminant retention and out turn infiltration of contaminants. 139

9 3.1.6 Impact of the vadose zone media (I) The vadose zone is defined as that zone above the water table which is unsaturated or discontinuously saturated, lying between soil layer and water table. The vadose zone s influence on aquifer contamination potential is essentially similar to that of aquifer media, depending on its permeability and on the attenuation characteristics of the media (Allison et al., 1994). If the vadose zone is highly permeable, then this may lead to a high vulnerable rating. The vadose zone was identified from the lithology of each drilled well of the study area. The vadose zone is composed of black or dark brown sandy loam and weathered granitic felsic gneiss rocks. Using the combination of vadose zone (4) and the DRASTIC weight (5), the index number (IrIw) was determined as shown in Table 7. Table 7: Range, Rating and Weight for Vadose zone Aquifer media Rating Index Weathered granite with sandy clay and gravel 5 25 Sand mixed with carcareous clay 4 20 Grey-Brownish clay with sand calcareous clay 3 15 DRASTIC Weight = Hydraulic conductivity (C) The hydraulic conductivity of an aquifer is a measure of the aquifer s ability to transmit water when submitted to a hydraulic gradient. It is a critical factor because it controls the velocity of groundwater flow; which in turn controls the velocity of contaminant flow within the aquifer. An aquifer with high conductivity is vulnerable to substantial contamination as a plume of contamination can move easily through the aquifer (Atiqur, 2008). According to DRASTIC model (Aller et al., 1985), these values fall in the same category and have the same rating. Therefore a local scale was assigned for the rating as shown in Table 8. A higher rating is indicative of higher hydraulic conductivity. Table 8: Range, Rating and Weight for Hydraulic Conductivity in the study area Range (%) Rating Index DRASTIC Weight = 1 The study area has a moderate hydraulic conductivity ranging from md -1. However, the central part of the study area (i.e. East and southwest of pump house) has a higher conductivity compared to the rest of the modeled area in the study area.the higher conductivity can be caused by the highly porous media of an aquifer (i.e., highly fractured aquifer media). This implies that high conductivity will be associated with high contamination potential once a pollutant reaches an aquifer Vulnerability map A groundwater vulnerability analysis was carried out combining the hydro-geological setting parameters results in a range of numerical values termed DRASTIC index. Derived by 140

10 combining the seven DRASTIC parameters index values, a range of values are developed that have been classified to present groundwater vulnerability. According to the DRASTIC model index, the aquifer vulnerability ranges from 87 to 136. The values were categorized into five classes as shown in Table 9 below. Table 9: DRASTIC Index values in the study area DRASTIC Index Value Vulnerability zone Extremely low Low Moderate High Extremely high Figure 4 indicates that in the south east and small area around the pump house, the vulnerability to contamination risk ranges between high and extremely high of the modeled area. These classes were found in the Makutupora ward (which covers a small area due to highly fracture of the aquifer media) and Chihanga ward, with high recharge potential and shallow water table. These areas require a particular attention. To the north, east and southwestern part of the Makutupora ward, vulnerability to contamination risk ranges between low and extremely low of the modeled area. Figure 4: Groundwater vulnerability map 141

11 3.1.9 Single parameter sensitivity analysis The single parameter sensitivity analysis was performed to evaluate the impact of each of the DRASTIC parameters on the vulnerability index. The single parameter sensitivity analysis is normally used to compare the "theoretical" weight of each input parameter in each polygon with their "effective" weight assigned by the analytical model. The "effective" weight is a function of the value of the single parameter with regard to the other six parameters as well as the weight assigned to it by the DRASTIC model (Atiqur, 2008). The "effective" weight of each polygon is obtained using the following formula: 1.3 Where W refers to the "effective" weight of each parameter, Pr and Pw are the rating value and weight of each parameter, and V is the overall vulnerability index. The "effective" weights of the DRASTIC parameters obtained in this study exhibited some deviation from that of the "theoretical" weights. Table 10 reveals that the depth to water table, aquifer media, topography and hydraulic conductivity are the most effective parameters in the vulnerability assessment because their mean effective weights of 22.14%, 19.92% 8.44 % and 16.01% respectively were higher than their respective theoretical weight. The rest of the parameters exhibit lower effective weight compared to the theoretical weights. The significance of depth to water table, net recharge and topography layers highlights the importance of obtaining accurate, detailed, and representative information about these factors. The depth to water on effective weight is slightly different compared with that of theoretical weight. Table 10: Statistics of the single parameter sensitivity analysis Single Parameter Sensitivity Analysis Parameter Theoretical Weight Theoretical Weight (%) Effective Weight (%) Mean Minimum Maximum D R A S T I C Sensitivity analysis of the DRASTIC Model Table 11 presents a statistical summary of the seven rated parameters of the DRASTIC model to work out the vulnerability of groundwater in the study area. An examination of the means of the parameters reveal that the highest risk of contamination of groundwater in the study area originates from the topography and aquifer media (mean value is 8.43 and 6.36). The impact of vadose zone, depth to water, and recharge imply moderate risks of contamination (mean values are 3.99, 3.79, and 4.09 respectively), while hydraulic conductivity (mean value is 2.96) and soil media (mean value is 2.79) impose a low risk of aquifer contamination. SD 142

12 Table 11: Statistical summary of the DRASTIC parameter maps A Statistical Summary of the DRASTIC Parameter Maps D R A S T I C Minimum Maximum Mean SD CV (%) The coefficient of variation (CV) indicates that a high contribution to the variation of vulnerability index is made by the recharge (55.01%) and hydraulic conductivity (44.24%). Moderate contribution is made by the topography (24.32%) and depth to water table (33.77%), while impact to vadose zone (8.77%), soil media (13.98%), and aquifer media (8.33%) are the least variable parameters. The low variability of the parameters implies a smaller contribution to the variation of the vulnerability index across the study area. 4. Conclusion and recommendations This study has shown that the depth to water table, aquifer media, topography and hydraulic conductivity are the most effective parameters in the vulnerability assessment because their mean effective weights of 22.14%, 19.92% 8.44 % and 16.01% respectively were higher than their respective theoretical weight. The significance of depth to water table, net recharge and topography layers highlights the importance of obtaining accurate, detailed, and representative information about these factors. Further to that, an examination of the means of the parameters reveal that the highest risk of contamination of groundwater in the study area originates from the topography and aquifer media (mean value is 8.43 and 6.36). The impact of vadose zone, depth to water, and recharge imply moderate risks of contamination (mean values are 3.99, 3.79, and 4.09 respectively), while hydraulic conductivity (mean value is 2.96) and soil media (mean value is 2.79) impose a low risk of aquifer contamination. The most important hydro-geologic parameters that contribute to groundwater vulnerability in this study area is a combination of hydraulic conductivity, shallow depth to water, topography with low percent slope, and net recharge. These results emphasizes that the model can be used as a tool for making decisions on the present and future land use of the study area, which may pose the greatest potential for contaminating groundwater resources. 5. References 1. Aller, L., Truman, B., Lehr, J. H., and Petty, R. J. (1985), DRASTIC-A Standardized System for Evaluating Groundwater Pollution Potential Using Hydrogeologic Settings. U.S. Environmental Protection Agency, Rober S. Kerr Environmental Research Laboratory, Office of Research and Development, EPA/600/2-85/ Allison, G. B., Gee, G. W., and Tyler, S. W. (1994), Vadose-zone techniques for estimating groundwater recharge in arid and semiarid regions. Soil Science Society of America Journal, 58(1), Arzu F. E. and Gültekin F. (2013), DRASTIC-based methodology for assessing groundwater vulnerability in the Gümüshaciköy and Merzifon basin (Amasya, Turkey), 143

13 4. Atiqur, R. (2008), A GIS based DRASTIC model for assessing groundwater vulnerability in shallow aquifer in Aligarh, India. 5. Babiker, I. S., Mohamed, A. A., Mohamed, T. H. and Kikuo, K. (2004), A GIS-based DRASTIC model for assessing aquifer vulnerability in Kakamigahara Heights, Gifu Prefecture, central Japan. 6. Gogu, R.C. and Dassargues, A. (2000), Current trends and future challenges in groundwater vulnerability assessment using overlay and index methods. Environmental Geology, 39 (6), pp Mato, R. and Mujwahuzi, M. (2010), Groundwater Governance Tanzania. 8. Murali, K. and Elangovan, R. (2013), Assessment of Groundwater Vulnerability in Coimbatore South Taluk, Tamilnadu, India Using Drastic Approach. International Journal of Scientific and Research Publications, 6(3), pp Ngana, J., Mahay, F. and Cross, K. (2010), Wami basin: a situation analysis. IUCN. 10. Ramesh, K. and Elango, L. (2011), Ground water quality and its suitability for domestic and agricultural use in Tondiar river basin, Tamil Nadu, India 11. Rwebugisa, R. A. (2008), Groundwater Recharge Assessments in Makutupora Basin, Dodoma Tanzania. Master of Science Thesis in Geo-Information Science and Earth Observation, International Institute for Geo-Information Science and Earth Observation, Enschede. The Netherlands. 12. Robins, N. S., MacDonald, A. M., and Allen, D. J. (2007), The vulnerability paradox for hard fractured Lower Palaeozoic and Precambrian rocks. Groundwater Vulnerability Assessment and Mapping. International Association of Hydrogeologists Selected Papers. Taylor & Francis Group, London, 11, pp Shindo, S. (1990), The study on the Recharge Mechanism and Development of Groundwater in the Inland Area of Tanzania. Progress Report of the Japan-Tanzania joint Research 2. Chiba University, Chiba, Japan. 14. Shindo, S. (1991), The study on the Recharge Mechanism and Development of Groundwater in the Inland Area of Tanzania. Progress Report of the Japan-Tanzania joint Research 3. Chiba University, Chiba, Japan. 15. Foster, S. (2007), Aquifer pollution vulnerability concept and tools use, benefits and constraints. Groundwater vulnerability assessment and mapping. IAH-selected Papers, 11, Thomas H. and Lear W. (2001), Assessing Vulnerability of groundwater. (Vol. 3), 17. Thorp, J. and Smith, G. D. (1949), Higher categories of soil classification: order, suborder and great soil groups. Soil Science, 67(2), pp United States of America-National Research Council (1993), Groundwater Vulnerability Assessment: Predicting relative contamination potential under conditions of uncertainty. National Academy. 144

14 19. Wood, W. W. (1999), Use and misuse of the chloride-mass balance method in estimating gr 145