Site-specific condition evaluation for managed aquifer recharge (MAR) site selection in granitic aquifers, Ghana

Water Supply Vol 24 No 5, 1842 doi: 10.2166/ws.2024.087 © 2024 The Authors Site-specific condition evaluation for managed aquifer recharge (MAR) site selection in granitic aquifers, Ghana Albert Acheampong and Gibrilla Abassc a, *, Geophrey K. Anornub, Frederick Owusu-Nimob, Charles Gyamfib a Ghana Integrated Water, Sanitation and Hygiene Program, World Vision International, Savelugu, Ghana Department of Civil Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana c Isotope Hydrology Section, Ghana Atomic Energy Commission, Accra, Ghana *Corresponding author. E-mail: acheampongalbert@gmail.com b AA, 0000-0001-5656-9018 ABSTRACT Water has prominence over all the usable natural resources to humankind due to its very significance to human life. Approximately, 70% of Ghana’s populace relies on groundwater exploitation for freshwater consumption. Managed aquifer recharge is capable of sustaining water resources for all livelihood activities. Underperformance of MAR systems is often due to site-specific hydrogeological conditions turning out to be less favorable than anticipated. This study evaluates the site-specific conditions for MAR sites identification in granitic aquifers, integrating in situ hydrogeological factors and GIS-MCDA. One hundred and twenty-one datasets from different boreholes comprising hydro geophysics, borehole drilling and pump test reports were used. The constraint mapping results indicate 92% suitable for MAR application within the study area, implying available enormous bare lands for flooding recharge technique. The suitability analysis discloses that 48 and 51% of the studied area fall within very high and high suitable zones, respectively, showing convincing and great potential to support infiltration ponds for MAR technology application. The valuable information provided through this study can serve as a guide for MAR implementation and for sustainable groundwater resources management within the Upper East region of Ghana. Key words: conditions, evaluation, Ghana, granitic aquifers, MAR sites, site-specific HIGHLIGHTS • • • • • The most important need and issue for a MAR scheme is the proper site evaluation. Availability of enormous bare lands for flooding recharge technique. The area has very large suitable areas for MAR due to its rural scattered settlements. The in situ hydrogeological information is comparatively very comprehensive and highly reliable. Guide for MAR implementation and sustainable groundwater resources management. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/). Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1843 GRAPHICAL ABSTRACT 1. INTRODUCTION Since it is very significant for human livelihood, water has prominence over all the usable natural resources to humankind. Access to potable water is extremely important for life’s sustenance. The earth possesses sufficient water in diverse forms to satisfy the natural demand, i.e. a range of 107 km3 is what many estimates have captured as the earth’s usable fresh groundwater (Fetter 2001). Approximately, 70% of Ghana’s populace relies on groundwater exploitation for freshwater consumption (Obuobie et al. 2018) because it is widely fit for purpose and not vulnerable to degradation like surface waters. Thus, for SDG 6 to be attained, groundwater abstraction ought to be aggressively pursued, because, on earth, it forms over 96% of the readily obtainable freshwater (Fetter 2001). The available water resources within the earth’s subsurface and surface water resources are going through intense stress due to technology advancements, population increment and climate change, resulting in soaring water demand (Evans & Sadler 2008; Cosgrove & Loucks 2015). In lessening the myriad water needs pressures, policymakers are trying to augment water supplies through groundwater resource development (Niswonger et al. 2017). Groundwater resources are widespread, least prone to droughts and quality deterioration and the least regulated water resource. Managed aquifer recharge is a groundwater engineering method, capable of sustaining water resources for all livelihood activities since MAR has shown that it can potentially recharge aquifers and augment groundwater supplies over time (Kwoyiga & Stefan 2019). MAR is simply meant to: divert, transport, replenish and store excess surface water in the aquifer in wet seasons, and later abstracted to be used in dry seasons (Sprenger et al. 2017). Before MAR scheme development, planning is extensively undertaken to guarantee their long-term sustenance (Sallwey et al. 2019). Suitable MAR site selection is an extremely important phase in the MAR planning stage because the located site determines the refill method, and the working and maintenance characteristics, like the efficiency of recovery and the amount of infiltration (Russo et al. 2015; Dillon et al. 2020). The most important need and issue for a MAR scheme (Kwoyiga & Stefan 2019) is the proper site evaluation. This refers to doing the necessary assessment of requirements for prospective areas, and proposing a location founded on a correct land evaluation. The Upper East region is in the Sudan Savannah and has distinct elevated temperatures and evapotranspiration. This forms part of Ghana’s driest zones (Yiran et al. 2016; Owusu et al. 2017). It records the least rainfall amount according to Logah et al. (2013). Groundwater is the alternative water supply preferred within the area due to its easy presence and wholesomeness. Groundwater remains the single feasible and economical quality water for such scattered rural settlers Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1844 (Dapaah-Siakwan & Gyau-Boakye 2000). Agriculture remains the most essential economic activity within the study area; therefore, the populace depends primarily on groundwater for their daily needs and irrigation usage, enhanced economic growth (agricultural productivity), increased sanitation and hygiene practices, education and health gains. MAR has so many recharge methods, hence very much easily adjustable to different locations that possess varying sitespecific properties. MAR locations suitability studies mostly focus on the inherent properties such as the slope, hydrogeology, nature of soil, storage ability and aquifer properties. The groundwater replenishment, storage and transmission processes are influenced by these parameters (Sallwey et al. 2019). Less conducive than envisaged distinctive hydrogeological site conditions contribute most often to the underperformance of numerous MAR systems (Maliva et al. 2015; Ringleb et al. 2016). Therefore, it is crucial to understand, evaluate and contextualize these conditions for the study, which demands a high priority before embarking on any groundwater augmentation process for sustainable groundwater development and management. This study evaluates the site-specific conditions for MAR sites in granitic aquifers in three districts (Garu Tempane, Bawku West and Kassena Nankana) in Upper East, Ghana. Groundwater is pervasive, least prone to contamination and the least regulated. Documented studies in UER reiterate that groundwater resources to be recharged in earnest since they are under intense stress and their sustainability is in danger (Kwoyiga & Stefan 2019). Erratic and scanty safe water supply for irrigation, industrialization and household activities as a result of surface water and wells drying up, which highly impedes agriculture activities and hence their economic empowerment (Ministry of Food and Agriculture 2019). 2. METHODOLOGY 2.1. Study area description The study was carried out in three districts in the Upper East region in Ghana namely Kassena Nankana, Garu Tempane and Bawku West districts. These districts are in the ‘Sudan Savannah climate region’ having distinctively high evapotranspiration and temperatures (Yiran et al. 2016). The region experiences a unimodal rainfall pattern, which lasts between 4 and 6 months (May–June to September–October), with a long dry season of 6–8 months yearly (Ghana Meteorological Agency 2020). The average rainfall amount is between 800 and 860 mm per annum. March–April records the highest monthly average temperature of 40°C, whilst the lowest average temperature (18°C) occurs in December to January (Ghana Meteorological Agency 2020). It records the least amount of rainfall in the interior savannah (Ghana Meteorological Agency 2020). Due to the dry climatic conditions of the place, the most economical and viable potable water source for the dispersed and rural communities in these districts is groundwater (Gyau-Boakye & Dapaah-Siakwan 1999). The significant economic activity is agriculture and the populace depends mainly on groundwater for daily use and irrigation activities (Ministry of Food and Agriculture 2019). Geologically, the study area is underlain by igneous rocks (granitoid of ‘Tamnean’ Plutonic Suite) (Geological Survey of Ghana 2009). This comprises minor quartz diorite, minor granodiorite and tonalite as depicted in Figure 1. This area is largely of silty sandy clay topsoil (lateritic sandy gravels in completely cemented clay binder – hardpan). Following this is the micaceous regolith (sand with silt and quartz gravels), and underlying this is the hard bedrock of granitoid (Acheampong 2017). It has a shallow depth to groundwater, which varies between 12 and 25 m deep from the ground surface with a few exceptions (Acheampong 2017). Drilled logs, up to 50 m depth, from World Vision Ghana confirmed a three-layered profile in the districts: topsoil, regolith and bedrock. 2.2. Data collection Groundwater data for the study were compiled from drilled borehole test reports obtained as part of the Ghana Integrated – Water, Sanitation and Hygiene (GI-WASH) Program between the period of 2014–2019. One hundred and twenty-one borehole information from hydro geophysics, borehole drilling and pump test results were used for this study. Fifty of Bawku West, 40 of Garu Tempane and 30 of Kassena Nankana datasets were used. Electrical resistivity measurements, i.e. vertical electrical sounding (VES) survey were used. Probing depths ranged from 50 to 90 m, and the dipole–dipole configuration was employed. Contained in the VES field report were relevant details like the date of the survey, identity of the community, probing depth, well reference, apparent resistivity and resistance, etc. Logs of the drilling were obtained from the drill reports. These logs were diligently done in the course of drilling by a competent hydrogeologist. Some of the common information that can be derived from the drill logs are well ID, drilling date, depth of the well, airlift yield, water strike, lithologies and sub-surface layers’ thicknesses, well design and construction, penetration rate, GPS coordinates. The pump test reports also had necessary information like borehole yield, discharge rate, etc. Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1845 Figure 1 | Geology map of the study area with drilled wells. 2.3. Data analyses The relevant data for the study were carefully extracted and validated from the three datasets. Spatial analysis of the extracted information was done using ArcGIS 10.3. This makes it possible to interpolate established groundwater quality characteristics and the estimated numerous indices of water quality for the entire area, the kriging interpolation technique was used. This technique is extensively used, as it quantifies data variance and gives stochastic modeling to provide precise estimates, hence making it the preferred interpolation method to others (spline and inverse distance weighting method (IDW) (Gentile et al. 2012; Forkuor et al. 2013). The kriging method gives better resolution with normally distributed data. Therefore, in the geostatistical analyst tool, the data were explored to examine normality (using histogram and QQ plot) and a transformation method (log or box-cox) was then applied to a skewed distribution. Then in the geostatistical wizard, the ordinary kriging method was applied to predict values for the unsampled locations. The semi-variograms (Gaussian, exponential, spherical and circular) and model parameters (partial sill, lag size and nugget) in the wizard were experimented with to select the best-fit model. Finally, the best-performing model was assessed (through rotation estimation). A model with cross-validation of root mean square standardized error (RMSE) of almost 1 and a mean error (ME) close to 0 indicates an accurate result and was therefore selected to create a spatial map. Datasets of 30 m resolution on ASTER digital elevation model (DEM) and Landsat 8 OLI level 1 were extracted from the United States Geological Survey (USGS) website. ArcGIS 10.3 processed and analyzed the DEM to produce a slope map. A raster image was produced using a 250 m resolution soil map containing soil infiltration rate information, from FAO world soil data in a shapefile format. Validation of the FAO soil texture information was done using the drill logs in situ soil data extracted from World Vision Ghana, GI-WASH Program. Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1846 Geostatistical analysis was then used to model the spatial distribution of the well yield, specific capacity, transmissivity and aquifer thickness to create spatial maps using the geostatistical analyst tool in ArcGIS 10.3. 2.4. Surface criteria The study area’s assessed factors under this were topography, soil nature and regolith thickness. These parameters were extracted from the geophysics and drill logs data. Aquifers get replenished from precipitation (direct seepage) into the vadose sections and decomposed outcrops. The common net recharge component of areas with no connecting interflow aquifers or surface waters or where no enormous water quantities are used is direct seepage (Ewusi et al. 2017). Topography is a very significant recharge evaluation parameter since it has a great bearing on the quantity of surface runoff generated against the infiltration rate, the precipitation rate and the water displaced speed of the water on the same surfaces (Ewusi et al. 2017). Gentle slopes are usually given high ratings: surfaces that rainwater under gravity cannot be easily displaced or halted in outlets favoring seepage. The soil type and thickness typically affect the slope. This may indirectly affect the hydrogeological system’s attenuation spirit. The slope map was generated with ArcGIS 10.3 and the 30 m resolution DEM. The DEM exportation to ArcGIS was done using the spatial analyst tool (‘slope’), thereafter a spatial slope map in percentage rise was generated (Figure 2). Zones with less than 10% slopes from previous studies have been proven to extend the residence time of surface water to permit infiltration (Rahman et al. 2012; Steinel et al. 2016). The study area revealed slopes ranging between 0 and 58%, and this was classified into four (Figure 2). This implies that the study area generally has low to medium topographic slopes, with satisfactory potential for groundwater recharge by direct infiltration from precipitation. The nature of the soil (S) plays a significant part in evaluating groundwater recharge inherent properties. It has restriction potential to water vertical flow into the ground. The soil textural characteristics may also lead to soil infiltration and permeability decrease, and this can influence groundwater recharge. The soil layer infiltration potential determines the given rate, with sand having high capacity and decreases as it graduates toward clay. The results from the area showed greater portions with loamy and sandy soil media relative to clay as shown in Figure 3, hence the likelihood to have high infiltration potential for MAR application. Regolith generally refers to the entire weathered zone in the study area and represents the zone just above the fresh bedrock and beneath the topsoil. The characteristics of the weathered product and thickness greatly control the groundwater quality, Figure 2 | Topography map of the study area. Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1847 Figure 3 | Soil map of the study area. porosity and permeability intensity, and subsequently groundwater replenishment. Deeper regolith thickness levels imply longer water travel times into the aquifer (groundwater). Therefore, during and or after rainfall, the areas with shallow regolith thickness, and in effect less water table depths most likely get recharged than thicker depths. The regolith thickness varies from 4 to 41 m, and a mean of 25 m (Figure 4). From the findings, the areas thus have shallow regolith thickness generally, therefore the tendency to have increased groundwater recharge with less travel time, and ideal for MAR. Figure 4 | Regolith thickness map of the study area. Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1848 2.5. Subsurface criteria The sub-surface criteria determine the water accumulation and transmittable capacities beneath the ground surface. The aquifer ought to be of good and moderate storage: concerning its porosity and formation thickness (Hofkes & Visscher 1986; Murray 2008) and can easily transmit water. The hydrogeological indicators: well yield, specific capacity, transmissivity and aquifer thickness were considered here in the study and were derived from the pumping test data. The specific capacity (SC) represents the pumping rate/yield (Q) concerning the drawdown (s) of the well and measured in l/m2. It is a very valuable number and can be used to furnish the design pumping rate or maximum yield for the well (from Equation (1)). It depends on the distribution of the pores, their shape and grain size. SC ¼ Q s (1) Figure 5 shows the area’s specific capacity distribution, to be chiefly high to moderate. It showed an average of 8 l/m2, with the highest figure of 18 l/m2 and the lowest value of 2 l/m2 over the study area (Figure 5). The medium to high specific capacity values signify very good capabilities of the area aquifers to support MAR application. Hydraulic conductivity (K ) and or transmissivity (T ) determines the groundwater flow rate at a given hydraulic gradient (Equation (2)). The aquifer unit discharge and flow speed is controlled by this parameter, and it is most often given as m2/s, m2/day or l/day. T ¼ Kb (2) K is the hydraulic conductivity in m/s, m/day, etc. and b (aquifer saturated thickness in m). b is the same as a confined aquifer thickness, and an unconfined aquifer means saturated section depth. The study area T distribution (Figure 6) ranges from 0.6 to 9 m2/day and has a mean of 3 m2/day. Likely the area has medium to high transmissivity figures, which is an indication of a very good groundwater flow rate, and water content within the aquifer unit, and hence great property for optimal site for MAR operation. Figure 5 | Specific capacity map of the study area. Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1849 Figure 6 | Transmissivity map of the study area. b (aquifer saturated thickness in m) is the same as the confined aquifer thickness, and an unconfined aquifer means saturated section depth. It has the potential for storing water. Both consolidated and unconsolidated rocks may usually serve as aquifers since they have water-storing potential. The availability of joints and fractures in these rocks brings about, changes in their storage and permeability values. Figure 7 depicts the aquifer thickness distribution, shows to be generally high to moderate as anticipated. It has an average of 22 m and ranges between 10 and 31 m. This represents the zone of saturation, and therefore the aquifer storage potential. The higher the thickness, the more water storage ability and vice–versa. 2.6. Suitability mapping MAR project success depends on the site selection, hinged on various site-specific parameters, that are classified: (1) surface conditions which aid underground water infiltration and (2) subsurface conditions that control aquifer water accumulation and transmission abilities of the areas (Maliva et al. 2015; Ringleb et al. 2016; Sallwey et al. 2019). Every parameter reclassification (into appropriate classes) was done using GIS. The Jenks Natural Breaks which are naturally imbedded in the data were used (de Smith et al. 2015). Then with the use of a general scale: (0–5), with 0 ¼ restricted, 1 ¼ less suitable and 5 ¼ highly suitable, the standardization was done. Standardization aids in converting into the same scale every created criteria map for easier comparison (Yalew et al. 2016). 2.6.1. Constraint mapping Constraint mapping was conducted to screen out unsuitable areas for MAR due to environmental and or ecological factors, such as water source distance, settlement and an aquiclude presence (Rahman et al. 2012; Sallwey et al. 2019). This screening-out process was done using Boolean logic for the threshold determination to exclude these zones. The Boolean logic process implores the combination of binary maps by the use of ‘AND’ and ‘OR’ operators to screen out the non-feasible areas. Boolean logic uses ones (1) and zeros (0) only to develop a binary map in which the criterion values satisfying the defined threshold value are given 1, or otherwise a 0 to show the unsuitability of the area (Valverde et al. 2016). The constraint mapping in this study was done using the land use/cover map. Forest reserves, settlements, rivers and stream channels were screened out as unsuitable areas to construct an infiltration basin. This was to protect the environment, avoid resettlement and displacement and prevent clogging due to high sediment loads from riverbeds and streams (Bouwer 2002). Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1850 Figure 7 | Aquifer thickness map of the study area. Therefore, the Boolean logic was used to filter out these land areas; a scale of 0 was given to the unsuitable lands, and a value of 1 was assigned to cultivated land, woodland and small reservoirs for suitable areas as in Table 1. 2.6.2. Standardization This process ensures that all the maps are on a common scale before integration. This helps lessen dimensionality when integrating because the maps are distinct (in types and value range) like a classified map (soil map) or a figure map (e.g. transmissivity) (Rahman et al. 2012). Several methods of standardization have been used in many MAR Suitability studies to classify maps: a rating range of binary set from 1 to 5 (Owusu et al. 2017; Fuentes & Vervoort 2020), 0 to 10 (Singh et al. 2013; Vishwakarma et al. 2021), 0 to 2 (Steinel et al. 2016) and a fuzzy set with criterion values having a degree of membership between 0 and 1 (Rahman et al. 2012; Valverde et al. 2016). However, adopted for the current study is a binary set range from 0 to 2 by Steinel et al. (2016), which makes it easier to perfect the final map and vividly determine further areas for any investigation. Hence, the criteria maps were standardized into suitable (value 2), less suitable (value 1) and unsuitable (value 0) which portray high to very high potential, minimal to medium potential and no to least potential, respectively, for MAR. Table 1 | Land use/cover constraint mapping criterion Area (km2) Land use/cover Boolean logic Kassena Nankana Area (%) Garu/Bawku Kassena Nankana Garu/Bawku Water bodies 0 4.90 14.37 0.6 0.7 Trees 1 30.63 35.37 4.0 1.7 Crops 1 17.69 117.14 2.3 5.6 Built-up 0 28.25 233.83 3.7 11.1 Rangeland 1 686.24 1703.30 89.4 81.0 Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1851 Based on their water infiltration rate and susceptibility to flooding, five soil textures were reclassified and ranked (Table 2) for the study area. Ranked 5 was loamy sand with high infiltration capacity of 34.17 cm/day, and covering the largest land area (93 and 53% for Kessena and Garu Tempane/Bawku West, respectively), considered ideal for MAR (Rahman et al. 2012). Clay was given a value of 0, the least option desirable due to its very high water-holding capacity. The study area has regolith thickness varying from 4 to 41 m, and a 25 m mean value. The least regolith thickness was from 4 to 18 m and ranked 5 (the highest) whereas the range of 31–41 m was given the lowest value of 1 (Table 2). The area Table 2 | Criteria standardization for site suitability analysis Kassena Nankana Criteria Class Garu Tempane & Bawku West Area (km2) Area (%) Scale Class Area (km2) Area (%) Scale Surface criteria Soil nature (cm/day) Clay 1.7 52.77 6.9 0 642.4 30.5 0 Loamy sand 34.17 714.93 93.1 5 1109.0 52.7 5 Sandy clay loam 7.68 230.1 10.9 1 Loam 13.28 68.8 3.3 3 Loam 7.77 53.7 2.6 3 Regolith thickness (m) Slope 14–16.5 235.42 30.7 4 3.8–18.2 190.15 9.0 5 16.5–19.8 306.67 39.9 3 18.2–23.3 231.98 11.0 4 19.8–27.2 193.26 25.2 3 23.3–27.4 641.19 30.0 3 27.2–31.9 32.35 4.2 2 27.4–30.9 565.23 27.0 2 30.9–40.9 475.44 23.0 1 (%) 0–5 712.4 92.8 5 0–5 2023.9 96.2 5 5.1–10 53.7 7 3 5.1–10 58.3 2.8 3 10.1–30 1.5 0.2 1 10.1–30 20.4 1 1 .30 0.1 0.01 0 . 30 1.3 0.1 0 9.98–12.2 143.86 18.7 1 16.3–21.3 264.83 12.6 3 12.2–16.3 226.18 29.5 2 21.3–23.5 562.28 26.7 4 16.3–17.9 269.77 35.1 3 23.5–25.9 967.62 46.0 4 17.9–19.1 87.55 11.4 3 25.9–31 309.27 14.7 5 19.1–22.3 40.34 5.3 4 3.5–3.8 61.71 8 3 0.6–2.9 952.08 45.3 2 3.8–4.0 379.19 49.4 3 3.0–3.8 667.27 31.7 3 4.0–4.2 75.41 9.8 4 3.9–4.7 351.28 16.7 4 4.2–4.6 251.38 32.7 4 4.8–8.8 133.37 6.3 5 2.0–3.8 26.65 3.5 1 3.7–6.9 381.05 18.1 1 3.8–5.8 54.24 7.1 2 6.9–9.3 1084.09 51.5 3 5.8–8.3 361.69 47.1 3 9.3–11.98 539.77 25.7 4 8.3–12.0 325.12 42.3 4 11.98–17.6 99.08 4.7 5 Subsurface criteria Aquifer Thickness Transmissivity Specific capacity (m) (m2/day) 2 (l/m ) Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1852 commonly has shallow regolith thickness, hence the tendency to have increased groundwater recharge with less travel time, and suitable for MAR. Slope variations between 0–3 and 3–5% are considered very high and high potential areas for optimum infiltration (Rahman et al. 2012; Steinel et al. 2016; Sallwey et al. 2019). Thus, these classes were considered suitable and assigned a value of ‘5’ and ‘3’ while slope intervals of 5–10% and greater than 10% were assigned ‘1’ and ‘0’, respectively (Table 2). Based on study area conditions, the recommended aquifer thickness for MAR ranges from 10 m (Rahman et al. 2012, 2013) to 20 m (Steinel et al. 2016). A least threshold of 20 m thickness was recommended to store sufficient water for the study area. Therefore, aquifer thicknesses from 20 to 26 m were given a scale of 4, and 5 was given to thicknesses above 26 m (Table 2). Krâsny (1997) classification was adopted for transmissivity standardization. 4.8–8.8 m2/day is the highest transmissivity value recorded whereas the least is between 0.6 and 2.9 m2/day, not considered ideal to sustain MAR. In this light, a rank of 5 was given to transmissivity values varying from 4.8 to 8.8 m2/day, 4 was given to values between 3.9–4.7 and 0.6–2.9 m2/day was assigned 2. The specific capacity values for the study area range from 2.0 to 17.6 l/m2, and 11.98–17.6 l/m2 was assigned a scale of 5 being the highest and most suitable for MAR. Values between 2.0 and 3.8 l/m2 which are the lowest were given a scale of 1 since it is perceived to have low sustenance for MAR. 2.6.3. Analytical hierarchy process AHP acts as a platform to make decisions; it is widely recognized and employed in several spatial analyses (GIS-based MCDA integrated) studies (Bandyopadhyay et al. 2009; Motuma et al. 2016; Yalew et al. 2016). Different criteria weights were calculated using AHP, through a pairwise comparison matrix which takes into account the criteria comparative significance. The matrix is created using two at a time and calculated on a numerical scale using sampled specialist views (Table 3). Based on the spreading method literature, seven specialist views were obtained and used for this study (Chowdhury et al. 2010; Owusu et al. 2017; Dupont 2018; Sallwey et al. 2019; Vishwakarma et al. 2021; Hussaini et al. 2022), for the pairwise comparison matrixes development. Equation (3) demonstrates how every pairwise matrix was calculated for each specialist view, with the pairwise matrix number equal to the number of specialists. The procedure for AHP: (a) Using the numerical scale from each specialist view. a pairwise comparison matrix (PCM) is developed, A1; the matrix’s number and size are equivalent to the specialists’ number and criteria, respectively, as in Equation (3). The matrix works using the reciprocity principle, given as aij and 1/aIj. A1 ¼ [aij ], i, j ¼ 1, 2, 3, . . . , n (3) (b) A new matrix B1 (Equation (4)) is then developed from the normalized matrix A1 with elements bij as in Equation (5). Using Equation (6), each criterion weight is then calculated. B1 ¼ [bij ], i, j ¼ 1, 2, 3, . . . , n (4) aij Bij ¼ Pn (5) i¼1 aij Table 3 | Pairwise comparison scale Scale Significance 1 Same 3 Medium 5 High 7 Very high 9 Extreme 2,4,6,8 Intermediate values Inverse Reciprocals comparison values Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1853 Pn i¼1 bij , i, j ¼ 1, 2, 3, . . . :n Wi ¼ Pn P n i j¼1 bij (6) The total components’ weights should be equal to 1 (Equation (7)): n X Wi ¼ 1 (7) i¼1 A relation between the highest eigenvalue (λmax) and its eigenvector (W ) of the matrix B1 is then developed (Equation (8)): (8) B1 W ¼ lmax W (c) The consistency ratio (CR) that shows the comparison’s consistency and quality is calculated (Saaty 1987) as in Equation (9). Equation (10) is used to compute the consistency index (CI): λmax is the highest eigenvalue with being the matrix sequence. Based on the matrix order, the random index is given (Table 4). CR ¼ CI RI CI ¼ lmax (9) n=(n 1) (10) 2.6.4. Weighted linear combination The creation of a suitability map through the parameters assemblage is the ultimate stage of the suitability analysis. For this study, the WLC overlay approach was employed, this is widely employed in site appropriateness analysis studies (Rahman et al. 2012; Sallwey et al. 2019). Using Equation (11) and WLC, the standardized thematic maps and their associated weights were overlaid to produce a composite suitability score. ArcGIS was employed for this purpose, using its inherent raster calculator tool. S¼ X (Wi xXi )x Y (11) Cj S represents the overall suitability score, Wi (the given weight), Xi (criterion index) and Cj (constraint parameter j value). 3. RESULTS AND DISCUSSION 3.1. Constraint mapping The constraint mapping results indicate 92% suitability (Table 1) for the application of MAR within the study area; this implies the availability of enormous bare lands for flooding recharge technique. Water bodies and cultivated lands (with crops and trees) constituted the suitable zones since these are areas where water impounding for flooding techniques can be carried out without destroying many properties or preserving them. Built-up areas and water bodies where human life and property destruction from recharge due to high precipitation runoffs and river currents made up the unsuitable zones. Due to the rural, scattered settlements nature and most lands being used for agricultural activities, the study area has very large suitable areas for MAR. Table 4 | Random consistency (RI) index n 1 2 3 4 5 6 7 8 9 10 11 12 RI 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49 1.51 1.54 0.1 or less consistency ratio is admissible: meaning a valid PCM, hence the weights are useable, and vice versa. Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1854 3.2. Assignment of weight The criteria weights were created using the AHP. In this, every view was singularly treated and for every criterion, the highest, mode and least weights were developed. A consistency ratio of less than 0.1 (Table 5) was achieved at a 95% confidence interval, signifying the reliability of the weights used. The most influential criteria for MAR spreading ranked in order of magnitude are transmissivity, aquifer storage/thickness, slope and specific capacity based on the mean values, with land use/cover being the least influential (Table 5). The spreading MAR is an infiltration method; thus requires sufficient storage capacity and this subsequently needs a transmissive aquifer. The hydrogeological properties indirectly relate to the geology and groundwater potential directly for a study area. This in situ information is comparatively very comprehensive and highly reliable, hence the very high weights associated with these factors (transmissivity, aquifer thickness and specific capacity) as anticipated. Theoretically and as envisaged, another very important surface feature in the spreading MAR method is the slope. This determines the surface runoff quantity that is produced against the infiltrate rate. Gentle slopes reduce surface runoffs and permit optimal infiltration into the underground aquifer, and vice versa for steeper slopes. In most site suitability analyses with the spreading method (Sallwey et al. 2019), the slope is often a prioritized factor. It is then justified that slope was given a higher weight in this study. The least weight in this study was the land use/cover (Table 5). This is because the study area has very large areas suitable for MAR (from the constraint mapping results), due to its rural scattered settlements. Hence, the lower weight would not alter the recharge process, and sway the final judgement. 3.3. Suitability analysis The map in Figure 8 is the weighted suitability analysis from the WLC. From Table 6, approximately 48% of the studied area falls within a very high suitable zone (50% of Kassena Nankana and 46% of Garu Tempane/Bawku West), and 51% (49% for Kassena Nankana and 54% for Garu Tempane/Bawku West) were in the high suitable zone. These areas show convincing and great potential to support infiltration ponds for MAR technology application, to help increase the groundwater quality as well as quantity within the study area. The moderate and low-suited zones constitute just about 1% of the total area (Table 6). 3.4. Suitability Map validation The reliability of the developed suitability map was assessed using existing borehole yields within the area (Figure 9). Past researchers (Forkuor et al. 2013; Verma et al. 2020) have established the relationship between borehole yield and recharge. Borehole yield (Q) gives the quantity of water that a borehole can produce in a time-space (m3/h or m3/day or L/m). It has a direct relationship to the stored groundwater volume (G) and aquifer permeability (K ) (from Equation (12)). The higher the yield, the more quantity of water a borehole/well could produce and vice versa (Harvey 2004). (12) Q ¼ f(G þ K) The validation was done by superimposing 102 functional borehole yields on the suitability map (Figure 8). Going by the Community Water and Sanitation Agency guidelines (CWSA 2014) for successful and unsuccessful boreholes, these borehole yields were grouped: ,12 L/min (low), 12–80 L/min (moderate) and high (.80 L/min). Table 5 | Pairwise matrix Criteria Slope LULC Soil texture Specific capacity Transmissivity Regolith thickness Aquifer thickness Slope 0.12 0.27 0.28 0.04 0.12 0.07 0.19 LULC 0.02 0.05 0.03 0.03 0.07 0.07 0.19 Soil texture 0.04 0.16 0.09 0.06 0.12 0.13 0.19 Specific capacity 0.37 0.22 0.19 0.11 0.12 0.03 0.05 Transmissivity 0.37 0.27 0.28 0.34 0.36 0.20 0.19 Regolith thickness 0.12 0.05 0.05 0.22 0.12 0.07 0.04 Aquifer thickness 0.12 0.05 0.09 0.45 0.36 0.34 0.19 λmax ¼ 7.70, CI ¼ 0.12, CR ¼ 0.09. Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1855 Figure 8 | MAR suitability map for the study area. Table 6 | MAR spreading method suitability scores ranking Kassena Nankana Garu Tempane & Bawku West 2 Suitability score Percentage of total area Total area (km ) Percentage of total area Total area (km2) Very high 49.8 382.37 45.5 483.48 High 47.8 366.99 54.3 577.38 Moderate 2.0 15.39 0.2 2.14 Low 0.4 2.92 The study area as revealed in Figure 9, largely disclosed medium to high well yields with a mean of 63 L/min and a range from 12 to 121 L/min. This points to the fact that the area generally has very good groundwater potential, storage abilities and permeability to act as a favorable site for future implementation of MAR technology. 4. CONCLUSION The current study has evaluated the site-specific conditions for managed aquifer recharge (MAR) sites in granitic aquifers in UER, (some districts) Ghana: with integrated use of in situ hydrogeological factors and GIS-MCDA. Six spatial maps (transmissivity, aquifer storage, slope, specific capacity, soil texture, regolith thickness and land use/cover) were overlaid to create the suitability map using the AHP method. The constraint mapping results indicate 92% suitable for MAR application within the study area, implying enormous bare land availability for flooding recharge technique. Based on the means from the AHP analysis, the most influential criteria for MAR spreading ranked in order of magnitude are transmissivity, aquifer storage/thickness, slope and specific capacity with land use/cover being the least influential. The suitability analysis discloses that 48 and 51% (of the total area studied) fall in high and very high suitable zones, respectively, showing convincing and great potential to support infiltration ponds for MAR Downloaded from http://iwaponline.com/ws/article-pdf/24/5/1842/1429356/ws024051842.pdf by guest Water Supply Vol 24 No 5, 1856 Figure 9 | Suitability map validation with the borehole yield. technology application. The results from the validation of the final map produced with borehole yields reveal generally very good groundwater potential, storage abilities and permeability to act as a favorable site for future implementation of MAR. The valuable information provided through current research could act as a reference point for MAR technology application, as policy makers can scale up this in other districts within the region. Further studies can leverage this for subsequent and future investigations for sustainable groundwater resources management in other areas within the Upper East region of Ghana. But in doing this, enhanced data spread, quality and quantity are required and recommended for subsequent work due to the limitations in the study approach. ACKNOWLEDGEMENT The authors are grateful to World Vision International, Ghana for the support in data provision for the research. DATA AVAILABILITY STATEMENT Data cannot be made publicly available; readers should contact the corresponding author for details. CONFLICT OF INTEREST The authors declare there is no conflict. REFERENCES Acheampong, A. 2017 Borehole Yield Estimation From Electrical Resistivity Measurements – A Case Study of Garu Tempane and Bawku West Districts, Upper East Region, Ghana. Unpublished MSc. Thesis, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. Bandyopadhyay, S., Jaiswal, R. K., Hegde, V. 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