American Journal of Water Resources
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American Journal of Water Resources. 2020, 8(4), 182-190
DOI: 10.12691/ajwr-8-4-4
Open AccessArticle

Groundwater Recharge Zone Mapping Using GIS-based Analytical Hierarchy Process and Multi-Criteria Evaluation: Case Study of Greater Banjul Area

Adama Gassama Jallow1, 2, , Djim M. L Diongue3, Huguette C. Emvoutou4, Daouda Mama1 and Serigne Faye3

1Abomey Calavi University, Benin

2Ministry of Petroleum and Energy, Banjul, Gambia

3Geology Department, Cheikh Anta Diop University of Dakar, Senegal

4Department of Earth Science, University of Douala, Cameron

Pub. Date: September 01, 2020

Cite this paper:
Adama Gassama Jallow, Djim M. L Diongue, Huguette C. Emvoutou, Daouda Mama and Serigne Faye. Groundwater Recharge Zone Mapping Using GIS-based Analytical Hierarchy Process and Multi-Criteria Evaluation: Case Study of Greater Banjul Area. American Journal of Water Resources. 2020; 8(4):182-190. doi: 10.12691/ajwr-8-4-4


Remote sensing (RS) and Geographic Information System (GIS) play a crucial role in understanding groundwater potential recharge in semi-arid areas. In this present study, groundwater recharge zone map is delineated for the shallow aquifer in the Greater Banjul Area (GBA) using GIS, RS and Multi-Criteria Evaluation (MCE) technique utilizing seven criteria (geology, land-use/cover, slope, drainage density, soil texture, groundwater fluctuation and aquifer transmissivity). Analytical Hierarchical Process (AHP) is used as MCE technique to normalize the weights of the various criterion. Each class of the different themes was assigned suitable score and normalized using a Fuzzy membership algorithm. Thematic layers were integrated using Weighted Linear Combination (WLC) in a GIS platform to generate groundwater recharge zone maps. The recharge map thus obtained was divided into four classes (poor, moderate, good, and very good) based on their influence to groundwater recharge. Results indicates that about 10.5 % of the total study area falls under ‘poor’ and ‘moderate’ zone and cover the estuarian portion of GBA, 40% of the total area falls under ‘very good’ zone which is a good indication for future artificial recharge planning and potential drilling of boreholes.

groundwater recharge zone multi-criteria evaluation greater Banjul area

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[1]  Shahid S, Nath SK, Ray J. (2000). Groundwater potential modeling in soft rock using a GIS. Int J Remote Sens 21:1919-1924.
[2]  Sener A, Davraz A, Ozcelik M. (2005). An integration of GIS and remote sensing in groundwater investigations: a case study in Burdur, Turkey. Hydrogeol J. 13: 826-834.
[3]  Solomon S, Quiel F. (2006). Groundwater study using remote sensing and geographic information system (GIS) in the central highlands of Eritrea. Hydrogeol J 14(5): 729-741.
[4]  Tabesh, M., & Hoomehr, S. (2009). Consumption management in water distribution systems by optimizing pressure reducing valves' settings using genetic algorithm. Desalination and Water Treatment, 2(1-3), 96-102.
[5]  Raju KCB. (1998). Importance of recharging depleted aquifers: State-of-the-art artificial recharge in India; J. Geol. Soc. India 51 429-454.
[6]  Chowdhury A, Jha MK, Chowdary VM. (2010). Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS, GIS and MCDM techniques. Environ Earth Sci 59(6): 1209-1222.
[7]  Agarwal, R., & Garg, P. K. (2016). Remote sensing and GIS based groundwater potential & recharge zones mapping using multi-criteria decision-making technique. Water resources management, 30(1), 243-260.
[8]  Todd DK. (1980). Groundwater hydrology, 2nd edn. New York, NY, p 535
[9]  Saraf AK, Choudhury PR. (1998). Integrated remote sensing and GIS for groundwater exploration and identification of artificial recharge sites. Int J Remote Sens 19(10):1825 1841
[10]  Malczewski J. (1999). GIS and multicriteria decision analysis. John Wiley & Sons, NY, p 392.
[11]  Ghayoumian J, Ghermezcheshmeh B, Feiznia S, Noroozi AA. (2005). Integrating GIS and DSS for identification of suitable areas for artificial recharge, case study Meimeh Basin, Isfahan, Iran. Environ Geol 47(4):493-500.
[12]  Agarwal, R., Garg, P. K., & Garg, R. D. (2013). Remote sensing and GIS based approach for identification of artificial recharge sites. Water resources management, 27(7), 2671-2689.
[13]  Chenini I, Mammou AB, May ME. (2010). Groundwater recharge zone mapping using GIS-based multi-criteria analysis: a case study in Central Tunisia (Maknassy Basin). Water Resour Manage 24(5): 921-939.
[14]  Singh, A., Panda, S. N., Kumar, K. S., & Sharma, C. S. (2013). Artificial groundwater recharge zones mapping using remote sensing and GIS: a case study in Indian Punjab. Environmental management, 52(1), 61-71.
[15]  Saaty TL. (1980). The analytical hierarchy process. McGraw Hill, NY.
[16]  Pawattana C, Tripathi NK. (2008). Analytical hierarchical process (AHP)-based flood water retention planning in Thailand. GIScience & Remote Sensing 45(3): 343-355.
[17]  Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.
[18]  Xu, Y.; Yu, L.; Feng, D.; Peng, D.; Li, C.; Huang, X.; Lu, H.; Gong, P. Comparisons of three recent moderate resolution African land cover datasets: CGLS-LC100, ESA-S2-LC20, and FROM-GLC-Africa30. Int. J. Remote Sens. 2019, 40, 6185-6202.