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Enzyme induced calcite precipitation (EICP), as a bio-cementation technique, has been used to improve the strength and stiffness of unstable soils. In this paper, the influence of key treatment conditions for EICP soil treatment such as curing temperatures (at 5°C, 25°C, 30°C and 50°C) as well as post-treatment conditions such as “oven-dried” (at 60°C) or “wet” (at room temperature, ~22°C) on the strength of EICP-treated sand were evaluated. The results from this study indicate that unconfined compressive strength (UCS), splitting tensile strength (STS), CaCO3 content (CC), the mass of precipitated CaCO3 (MCaCO3) and CaCO3 precipitation ratio (PR) increased with increasing curing temperatures during EICP soil treatment possibly due to the increase in urease enzyme activity at high temperatures. For similar CC, the “oven-dried” samples showed a significantly higher strength (i.e. UCS and STS) compared to the “wet” samples, possibly due to the transformation of unstable vaterite to a more stable form (i.e. calcite) during oven-drying. Scanning electron microscopy images and X-ray powder diffraction analysis showed that the “oven-dried” sample mainly produced calcite crystals while the “wet” sample produced a mixture of calcite and vaterite crystals. The results indicate that thermodynamically unstable vaterite crystals formed at low temperatures may be transformed into a more stable polymorph of CaCO3 (e.g. calcite) at high temperatures (~40 to 60°C), an indication of the higher strength achieved for the “oven-dried” samples

The occurrence of premature rockbolt failure in underground mines has remained one of the most serious challenges facing the industry over the years. Considering the complex mechanism of rockbolts’ failure and the large number of influencing factors, the prediction of rockbolts’ failure from laboratory testing may often be unreliable. It is therefore essential to develop new models capable of predicting rockbolts’ failure with high accuracy. Beyond the predictive accuracy, there is also the need to understand the decisions made by these models in order to convey trust and ensure safety, reliability, and accountability. In this regard, this study proposes an explainable risk assessment of rockbolts’ failure in an underground coal mine using the categorical gradient boosting (Catboost) algorithm and SHapley Additive exPlanations (SHAP). A dataset (including geotechnical and environmental features) from a complex underground mining environment was used. The outcomes of this study indicated that the proposed Catboost algorithm gave an excellent prediction of the risk of rockbolts’ failure. Additionally, the SHAP interpretation revealed that the “length of roadway” was the main contributing factor to rockbolts’ failure. However, conditions influencing rockbolts’ failure varied at different locations in the mine. Overall, this study provides insights into the complex relationship between rockbolts’ failure and the influence of geotechnical and environmental variables. The transparency and explainability of the proposed approach have the potential to facilitate the adoption of explainable machine learning for rockbolt risk assessment in underground mines.

Enzyme-induced carbonate precipitation (EICP) is a relatively new bio-cementation technique for ground improvement. In EICP, calcium carbonate (CaCO₃) precipitation occurs via ureahydrolysis catalysed by the urease enzyme sourced from plants. EICP offers significant potential forinnovative and sustainable engineering applications, including strengthening of soils, remediation of contaminants, enhancement of oil recovery through bio-plugging and other in situ field applications. Given the numerous potential applications of EICP, theoretical understanding of the rate and quantity of CaCO₃ precipitation via the ureolytic chemical reaction is vital for optimising the process.For instance, in a typical EICP process, the rate and quantity of CaCO3 precipitation can dependsignificantly on the concentration, activity and kinetic properties of the enzyme used along with the reaction environment such as pH and temperature. This paper reviews the research and development of enzyme-catalysed reactions and its applications for enhancing CaCO₃ precipitation in EICP. The paper also presents the assessment and estimation of kinetic parameters, such as the maximal reaction velocity (Vmax) and the Michaelis constant (Km), that are associated with applications in civil and geotechnical engineering. Various models for evaluating the kinetic reactions in EICP are presented and discussed, taking into account the influence of pH, temperature and inhibitors. It is shown that a good understanding of the kinetic properties of the urease enzyme can be useful in the development, optimisation and prediction of the rate of CaCO₃ precipitation in EICP. Refereed/Peer-reviewed

Bio-cementation, notably microbial induced calcite precipitation (MICP), and Enzyme induced calcite precipitation (EICP), binds soil particles together through calcium carbonate (CACO3) precipitation (cementation). Both MICP and EICP have significant potential for many scientific and engineering applications including improvement of strength, reducing soil liquefaction potential, surface erosion control, reducing permeability, and heavy metal contaminant remediation. However, the catalytic mechanism and the precipitation of CACO3in MICP and EICP mainly depends on the source of urease enzyme and the treatment process used. This study evaluates the mechanical and microstructural behaviour of bio-cementation using the standard MICP and EICP treatment process. The results indicate that, for the same number of treatment cycles (NTC), a higher amount of precipitated CACO3was achieved for MICP than EICP which affects the strength. For similar average CACO3content (AC), the standard treatment method used in EICP produced a higher chemical efficiency (defined as the amount of CACO3precipitated relative to the quantity of urea-CaCl2used) than in MICP. The results from scanning electron microscopy (SEM) imaging shows that the morphologies of the precipitated CACO3in MICP and EICP are similar, however, a high amount of vaterite was found in EICP than MICP. The outcome of this study indicates that the standard treatment processes used in MICP and EICP may influence the chemical efficiency, the amount, distribution, and polymorph of the precipitated CACO3which may directly affect the strength. Refereed/Peer-reviewed

Microbial-induced carbonate precipitation (MICP) and enzyme-induced carbonate precipitation (EICP) are two bio-cementation techniques, which are relatively new methods of ground improvement. While both techniques share some similarities, they can exhibit different overall behaviours due to the differences in urease enzyme sources and treatment methods. This paper presented 40 unconfined compressive strength (UCS) tests of MICP and EICP treated sand specimens with similar average calcium carbonate () content subjected to cycles of wetting-drying (WD), freezing-thawing (FT) and elevated temperature (fire resistance test – FR and thermogravimetric analysis – TG). The average content after a certain number of WD or FT cycles () and their corresponding UCS () reduced while the mass loss increased. The EICP treated sand specimens appeared to exhibit a lower resistance to WD and FT cycles than MICP treated specimens possibly due to the presence of unbonded or loosely bonded within the soil matrix, which was subsequently removed during the wetting (during WD) or thawing (during FT) process. FR test and TG analysis showed a significant loss of mass and reduction in content with increased temperatures, possibly due to the thermal decomposition of . A complete deterioration of the MICP and EICP treated sand specimens was observed for temperatures above 600 °C. The observed behaviours are complex and theoretical understanding is far behind to develop a constitutive model to predict . Therefore, a multi-objective evolutionary genetic algorithm (GA) that deals with pseudo-polynomial structures, known as evolutionary polynomial regression (EPR), was used to seek three choices from millions of polynomial models. The best EPR model produced an excellent prediction of with a minimum sum of squares error (SSE) of 2.392, mean squared error (MSE) of 0.075, root mean square error (RMSE) of 0.273 and a maximum coefficient of determination of 0.939. Refereed/Peer-reviewed

Refereed/Peer-reviewed Geological processes such as weathering and metamorphism normally lead to the destruction of primary physical features on rocks, making it difficult to accurately classify lithologies during manual core logging. As a result, manual core logging remains a subjective and inconsistent process. Machine learning techniques have shown tremendous success in lithological classification, but their performance has significant drawbacks, particularly in highly imbalanced data domains and complex geological terrain. Because there is an increasing demand for accurate and timely lithological classification, this study proposes an objective hybrid approach based on synthetic minority oversampling technique and extreme gradient boosting (SMOTE-XGB) for lithological classification within the Tarkwaian paleo placer formation using assay data obtained through X-Ray Fluorescence (XRF) analysis. Five other intelligent approaches were developed for comparative purposes to further evaluate the performance of the proposed approach, using accuracy (Acc), area under the curve (AUC), precision, sensitivity, and F1 score as evaluation metrics. The statistical results have proven that the proposed SMOTE-XGB approach is more efficient at classifying the Tarkwaian lithologies than the other machine learning models used in this study. When SMOTE was applied to the imbalanced dataset, the results revealed a significant improvement in the classification performance of the minority classes, particularly the mineralised lithologies. To that end, this research has shown that applying SMOTE to an imbalanced dataset can improve the prediction efficiency of machine learning models.

Refereed/Peer-reviewed Arsenic contamination is increasingly a serious global health concern, especially in developing countries like Ghana where the intensification of mining activities has resulted in adverse pollution of various water sources within mining communities. To harness the early detection of arsenic contamination in multiple water supply systems, this work aimed to assess and compare the prediction efficiency of different machine learning methods. Novel machine learning algorithms such as extreme gradient boosting (XGB), light gradient boosting (LGB) and generalized regression neural network (GRNN), which are yet to be explored in modelling arsenic concentration in various water supply systems (e.g. surface water and groundwater) were considered in this study. These models were compared with state-of-the-art machine learning methods of decision tree (DT), multivariate adaptive regression spline (MARS), multilayer perceptron neural network (MLP) and random forest (RF). The applied methods were evaluated using the coefficient of determination (R2), Nash–Sutcliff efficiency (NSE) and mean squared error (MSE). The statistical analysis showed that the newly tested models (XGB, LGB and GRNN) produced satisfactory predictions which were comparable to the state-of-the-art methods. Thus, all the methods applied including the newly introduced models have proven efficient in the arsenic modelling task with R2 > 0.93, NSE > 0.92 and MSE

Microbially induced calcium carbonate precipitation (MICP) and enzyme induced calcium carbonate precipitation (EICP) are the two most widely known bio-cementation techniques, particularly the former. EICP offers several benefits over MICP such as the smaller size of the urease enzyme making it applicable to a wider range of soils and simpler application processes. This review critically examines existing research on the EICP technique and provides an original meta-analysis of the available data. It is understood that factors such as the source and activity of the urease enzyme, the concentration of the chemical constituents (urea, calcium chloride and urease enzyme), the treatment approach used and the morphology of the precipitated calcium carbonate (CaCO3) may all affect the performance of the EICP treated material. Consequently, various enhancing additives including magnesium chloride (MgCl2), magnesium sulfate (MgSO4), zeolite, dried non-fat milk, xanthan gum, sisal fibre and cabbage juice have been utilised in recent studies to improve on the effectiveness of the EICP process. In this review, engineering parameters such as the unconfined compressive strength are correlated to the CaCO3 content (CC) and soil uniformity coefficient (Cus) for EICP treated soils using compiled data from previous literature. However, the strength of EICP-treated soil may also depend on the particular polymorph, contact location and distribution of precipitated CaCO3 as well as the soil particle size and shape. Refereed/Peer-reviewed

Monitoring of water quality through accurate predictions provides adequate information about water management. In the present study, three different modelling approaches: Gaussian process regression (GPR), backpropagation neural network (BPNN) and principal component regression (PCR) models were used to predict the total dissolved solids (TDS) as water quality indicator for the water quality management. The performance of each model was evaluated based on three different sets of inputs from groundwater (GW), surface water (SW) and drinking water (DW). The GPR, BPNN and PCR models used in this study gave an accurate prediction of the observed data (TDS) in GW, SW and DW, with the R2 consistently greater than 0.850. The GPR model gave a better prediction of TDS concentration, with an average R2, MAE and RMSE of 0.987, 4.090 and 7.910, respectively. For the BPNN, an average R2, MAE and RMSE of 0.913, 9.720 and 19.137, respectively, were achieved, while the PCR gave an average R2, MAE and RMSE of 0.888, 11.327 and 25.032, respectively. The performance of each model was assessed using efficiency based indicators such as the Nash and Sutcliffe coefficient of efficiency (ENS) and the index of agreement (d). The GPR, BPNN and PCR models, respectively, gave an ENS of (0.967, 0.915, 0.874) and d of (0.992, 0.977, 0.965). It is understood from this study that advanced machine learning approaches (e.g. GPR and BPNN) are appropriate for the prediction of water quality indices and would be useful for future prediction and management of water quality parameters of various water supply systems in mining communities where artificial intelligence technology is yet to be fully explored.

Expansive soils go through significant volume changes due to seasonal moisture variations resulting in ground movements. The ground movement related problems are likely to worsen in the future due to climate change. It is important to understand and incorporate likely future changes in design to ensure the resilience of structures built on such soils. However, there has been a limited amount of work quantifying the effect of climate change on expansive soils movement and related behaviour of structures. The Thornthwaite Moisture Index (TMI) is one of the commonly used climate classifiers in quantifying the effect of atmospheric boundary on soil behaviour. Using the long-term weather data and predicted future changes under different emission scenarios, a series of TMI maps are developed for South Australia. Potential changes in ground movement are then estimated for a selected area using a simplified methodology where the effect of future climate is captured through changes in TMI. Results indicate that South Australia is likely to face a significant reduction in TMI under all emission scenarios considered in this study. The changes in TMI will lead to a considerable increase in potential ground movement which will influence the behaviour of structures built on them and in some areas may lead to premature failure if not considered in the design Refereed/Peer-reviewed

Microbial-induced calcite precipitation (MICP)is a process that uses naturally occurring bacteria to bind soil particles together through calcium carbonate (CaCO3) precipitation. It is a promising new technology in the area of Civil Engineering with the potential to become a cost-effective, environmentally friendly, and sustainable solution to many problems such as ground improvement, liquefaction remediation, enhancing properties of concrete, and so forth.&nbsp

Enzyme induced carbonate precipitation (EICP) is a bio-cementation technique and is a new area of Geotechnical Engineering. In this paper, a parametric study was conducted to evaluate and optimize the effect of concentration and activity of urease enzyme and concentration of other chemical constituents (urea and calcium chloride) on EICP process. pH, electrical conductivity (EC), and micro-structure analysis using scanning electron microscope (SEM) imaging were performed. Results indicate that, the precipitation ratio (PR), which is defined as the ratio of mass of precipitated CaCO3 in test tube and theoretical mass of CaCO3 is a function of the concentration of urea-CaCl2 (mol/L) and urease enzyme (kU/L). Rate of change in pH and EC during urea hydrolysis is influenced by urea and urease enzyme concentration. SEM images of CaCO3 precipitates from solution containing low active urease enzyme (3,500 U/g) showed a disordered and anhedral calcite crystals whereas the high active urease enzyme (40,150 U/g) showed euhedral and agglomerated rhombohedral calcite morphology. Refereed/Peer-reviewed

The overall effectiveness of bio-cementation techniques such as microbial-induced carbonate precipitation (MICP) or enzyme-induced carbonate precipitation (EICP) can be different due to different sources of urease enzyme and treatment approach used. This paper compares the behaviour of oven-dried MICP and EICP-treated sand from macro- and micro-mechanical point of view with the number of treatment cycles and average calcium carbonate (CaCO3) content used as a comparison basis. The results indicate that in both processes, the calcium carbonate content increased with the number of treatment cycles and led to an improvement in strength (unconfined compressive and splitting tensile strength) and stiffness. For similar average calcium carbonate content, EICP-treated samples showed significantly higher splitting tensile strength (compared to MICP) even though a slightly smaller amount of precipitates were observed at particle contacts through scanning electron microscopy. This indicates, besides the average calcium carbonate content, its distribution along the height of the sample is likely to have a significant contribution towards the strength. X-ray powder diffraction and energy-dispersive X-ray spectroscopy analyses confirmed that precipitated calcium carbonate in both types of treatments were mainly calcite crystals with minor traces of aragonite.

Granitic aggregates are mostly used for civil construction and other engineering works in Ghana. In this project, the characteristics of the Cape Coast (G1) and Dixcove (G2) granitoids for sustainable road construction were assessed. Physical and mechanical properties of the rocks were evaluated. Hand specimen description revealed that, amphibole is the major mafic mineral in the G2 and biotite as the dominant mafic mineral in the G1 granitoids. Petrographic study of the grains showed that, the large grains interlocked with fine grains (well-graded) with irregular grain boundaries in the matrix of the G2 gives the rocks a higher strength to withstand compressive loads than the G1 granitoids which have micro fractures in them that acts as weak planes in the rock. Geotechnical tests performed on the rocks gave an average Aggregate Crushing Value (ACV) of 11.6 % for Dixcove and 20.1 % for the Cape Coast, Aggregates Impact Value (AIV) of 6.1 % for Dixcove and 11.02 % for Cape Coast, Aggregate Abrasion Value (AAV) of 16.60 % for Dixcove and 26.0 % for Cape Coast, Specific Gravity of 2.74 for Dixcove and 2.66 for Cape Coast and Water Absorption of 0.18% for Dixcove and 0.51 % for Cape Coast granites. These values indicate that, both rock aggregates have relatively high strengths. However, G2 granitoids have relatively high resistance to compressive stresses under crushing, impacts and abrasion of traffic loads hence more suitable for sustainable road construction according to the global standards.

The increase in engineering projects translates to an increase in demand for construction materials, for example, aggregates which are a major component in concrete works. There are many quarries in the Kumasi area which produce aggregates for use in construction works. However, there is no readily available information on the geological and geotechnical properties of these aggregates for use by engineers during the planning, design and construction of projects. This project therefore sought to characterise the aggregate from selected areas (close to some major quarries) in Kumasi based on their geological and engineering properties for construction purposes. Results of the study indicate that Aggregates from sampling locations KP and CS passed the FI test with those from CS being the only ones to pass for EI, making them the best aggregates in terms of Flakiness and Elongation Indices. The aggregates from all the sampling locations passed for the Specific Gravity and Water Absorption tests with CS aggregates giving the best results indicating high strength and good rate of water absorption. Aggregate from sampling location NM gave the best result for the Aggregate Impact Value test indicating high resistance to sudden impacts and shocks. With the Ten Percent Fines Value and the Aggregate Crushing Value Tests, CS yet again produced the aggregates with the best results. The aggregate gave a very high result even under the wet/soaked condition when all the others were giving very low results. Aggregates from this sampling locations can withstand loading gradual compression better than the rest. Finally, the KP aggregates gave the best results for the Los Angeles Abrasion Value which suggests such materials to be the hardest and toughest to resist crushing, degradation and disintegration. Aggregates from the CS, however gave the second best results. From the study, it was concluded that the most suitable location to obtain good quality aggregates is around CS as its aggregates gave the best results in almost all the tests.

Overcharging in rocks (wall faces) during blasting and excavation usually causes damage to rock mass in most mining and quarry industries. This creates blast-induced fractures which can relates with pre-existing fracture pattern thereby increasing sliding and rockfall from the crest and body of an excavated wall. The spacing and orientation of pre-existing fractures are predominant at a small-scale mining (galamsey) site at ‘Atta ne Atta', a town near Beposo, in the Western Region of Ghana. Geotechnical field studies were carried out to investigate the possibility of any instability within the area to eradicate the occurrence of an unexpected future wall failure (rockfall). The geotechnical mapping conducted was focused on fracture distribution and spacing. Mean spacing (Sm) of existing fractures was calculated and corrections were made to obtain calculated spacing (Sc). The scanlines of wall face 001 and wall face 002 intersect with their corresponding strike and dip at 78° and 80° respectively creating a slightly favourable fracture pattern and rock wall stability. The fracture pattern created at Wall Face 003 and Wall Face 004 were unfavourable for rock stability with their corresponding scanlines having a strike and sip of 67° and 73° respectively. The instability of these wall faces (003 and 004) is as a result of parallel orientation of the induced fractures to the strike of the pre-existing fractures. Observations made from the stereographic projections and rose diagram indicate a cluster of fracture patterns with a general strike of NNE-SSW. Hence, the fracture patterns in the study area are composed of favourable (stable) rock mass at some walls and unfavourable (unstable) rock mass at other wall faces due to overcharging of blast holes.

The quality of water in mining communities is uncertain since metals associated with acid mine drainage are known to saturate these waters. Previous studies in Tarkwa, an area noted for gold and manganese extraction, have reported large concentrations of aluminium, arsenic, cadmium, copper, lead, manganese and mercury in water samples. This research aimed at investigating the chemistry of groundwater with special focus on the contamination status of trace elements. It also compared levels of metal concentration with those that were determined in previous research works, to identify changes that might have occurred. Thirty-eight water samples from boreholes, hand-dug wells and streams, within the Tarkwa area were obtained and analysed. Results show that 90 % of water in the area is acidic and Eh was determined to be positive, depicting oxidizing conditions. Mean groundwater temperature was 28.9 ºC. Thirty-two samples had either temperature or pH values falling outside the range recommended by the World Health Organisation (WHO). Thirty samples had at least one metal concentration exceeding the WHO guideline values. Among the list of elements that exceeded the guideline, arsenic, manganese, nitrate, nitrite and iron were the most predominant. The dominant ions in the samples were sodium and bicarbonate. High concentrations of Fe and SO42- in some parts of the study area point to the influence of acid mine drainage (AMD). Comparisons of results of metal concentrations with findings from previous research in the area showed a reduction in concentration. Hydrochemical modelling with PhreeqC attributed this reduction to sorption processes. Comparison of levels of metal concentration in the different water supply facilities (borehole, hand-dug well and stream) showed no significant variations. Keywords: Water Quality, Drinking Water, Hydrochemical Modelling, Heavy Metals

usc Certain parts of Ghana (Eastern and Volta region) are predominantly covered by neoproterozoic Dahomeyide rocks which occurred during the Pan-African Orogeny event in West Africa. To understand the petrological, geochemical and structural evidence of this geologic event, a detailed geological mapping exercise was conducted in some parts of the Eastern and Volta regions of Ghana. The aim of this research is to understand the local geology of these areas and how it best fits the regional geology of Ghana and its implications in the Pan-African Orogenic event. The evidences presented in this study show that the rocks in these areas are mainly metamorphic, which are granitic augen gneiss, biotite gneiss and quartzite. The gneisses were proposed to belong to the basement Dahomeyan, while the quartzites belong to the Togo Structural Unit. It was also inferred that the rocks have been deformed mainly by brittle and ductile deformation, resulting in structures such as foliations, fractures and joints observed in the quartzites and gneisses within the area of study. The structures within the study area have a general attitude of north-east–south-west with some few structures trending in the north-west–south-east directions. Again, it was inferred that the rocks from the Dahomeyan structural unit are highly metamorphosed and deformed as compared to the rocks from the Togo structural unit. The granitic augen gneiss and biotite gneiss have rock-forming minerals such as biotite, K-feldspar, quartz, muscovite, plagioclase and hornblende in varying proportions, whereas the quartzites are predominantly composed of glassy quartz crystals. Refereed/Peer-reviewed

usc Flood is one of the most imperious natural hazards that can cause economic damages to infrastructures and natural ecosystems. In view of the extensive mining activities in the Tarkwa area, there has been an increase in human intervention of natural water bodies via degradation of vegetation in the watershed area, inappropriate land-use change, soil erosion and expansion of paved surface area for settlement and industrialisation. This has increased the degree of flood susceptibility within the area, with major flood incidents recorded on a timely basis. In this study, a GIS-based approach was utilised to delineate flood-prone zone within the Tarkwa mining area using Digital Elevation Models (DEMs). A DEM-derived morphologic features including local slope and streamflow network were developed using ArcGIS. The flood susceptible map was generated by merging the slope map and the stream network maps. The results indicate that about 42.59% of the study area were highly prone to flooding. The areas susceptible to flooding were mainly made up of agricultural lands with high usage of chemical fertilizers for farming, which may leach into nearby rivers, streams, lakes and groundwater during flood occurrence. It is understood from this study that the mining areas within the Tarkwa Nsuaem municipality were less susceptible to flooding. The outcome of this study provides a simplified method of mapping and assessment of flood susceptible areas which can be used as a reference for flood risk management, prevention, and reduction of natural disasters in the study area. Refereed/Peer-reviewed

Microbial-induced calcite precipitation (MICP) is a promising new technology in the area of Civil Engineering with potential to become a cost-effective, environmentally friendly and sustainable solution to many problems such as ground improvement, liquefaction remediation, enhancing properties of concrete and so forth. This paper reviews the research and developments over the past 25 years since the first reported application of MICP in 1995. Historical developments in the area, the biological processes involved, the behaviour of improved soils, developments in modelling the behaviour of treated soil and the challenges associated are discussed with a focus on the geotechnical aspects of the problem. The paper also presents an assessment of cost and environmental benefits tied with three application scenarios in pavement construction. It is understood for some applications that at this stage, MICP may not be a cost-effective or even environmentally friendly solution, however, following the latest developments, MICP has the potential to become one.

Groundwater vulnerability assessment to delineate areas that are susceptible to contamination from mining and anthropogenic activities has become an important element for resource management and landuse planning. In view of the extensive mining in the Tarkwa area, quality of groundwater has become an important issue. This study estimates aquifer vulnerability by applying the SINTACS model which uses seven environmental parameters to evaluate aquifer vulnerability and geographical information system (GIS) in the Tarkwa mining area. Sensitivity analysis has also been carried out to evaluate the relative importance of the model parameters for aquifer vulnerability. The SINTACS model results show that the intrusive rocks within the Tarkwaian and the Birimian rocks are dominated by very high vulnerability classes while the Banket Series is characterised by high vulnerability class. The Huni Sandstones have moderately high vulnerability. In addition, the Kawere Group and the Tarkwa Phyllites displayed medium vulnerability. Analysis from the variogram model shows that all parameters used in the SINTACS model have a strong spatial structure. From statistical analysis, depth to water parameter inflicted the highest impact on the vulnerability of the aquifer followed by effective infiltration, vadose zone media, soil media, aquifer media, topography and hydraulic conductivity in the order of decreasing impact. Sensitivity analysis indicated that the aquifer media, hydraulic characteristics and topography cause large variation in vulnerability index. Depth to water and effective infiltration were found to be more effective in assessing aquifer vulnerability. Keywords: Groundwater, Vulnerability, Tarkwa, SINTACS, GIS