Main Article Content

Abstract

Liberia is marked by poor and insufficient hydrogeological data due to limited studies coupled with years of civil instability. Although Montserrado County has abundant water resources, lack of adequate knowledge of the available water resources has led to unsustainable groundwater utilization as well as investment losses from drilling unsuccessful boreholes. This research therefore aims at blending remote sensing with GIS-based multicriteria analysis to delineate suitable groundwater potential zones. Remote sensing and conventional data were used to construct a groundwater potential zone (GWPZ) map by integrating lineament and drainage densities, geology, slope and elevation, soil, annual rainfall, land use land cover, and the normalized difference vegetation index (NDVI) maps of the study area. The Analytic Hierarchy Process (AHP) was used in assigning weights to each thematic map, according to its influence on groundwater accumulation, for their integration. The results reveal that slope, lineament density, drainage density, geology, and land use land cover are parameters with the most influence (about 68%) on groundwater recharge within the area. The result also shows that about 10 %, 25 %, 30 %, 25 %, and 10 % of Montserrado County has very high, high, moderate, low zone, and very low groundwater potential zones, respectively. The study, therefore, provides very useful information that may guide the development and management of the groundwater resources within the study area. 

Keywords

Groundwater Recharge Remote Sensing GIS Analytic Hierarchy Process

Article Details

References

  1. Abrams, W., Ghoneim, E., Shew, R., LaMaskin, T., Al-Bloushi, K., Hussein, S., AbuBakr, M., Al-Mulla, E., Al-Awar, M. and El-Baz, F. (2018). Delineation of groundwater potential (GWP) in the northern United Arab Emirates and Oman using geospatial technologies in conjunction with Simple Additive Weight (SAW), Analytical Hierarchy Process (AHP), and Probabilistic Frequency Ratio (PFR) techniques. Journal of Arid Environments, 157, pp.77-96.
  2. Adeyeye, O.A., Ikpokonte, E.A. and Arabi, S.A. (2019). GIS-based groundwater potential mapping within Dengi area, North Central Nigeria. The Egyptian Journal of Remote Sensing and Space Science, 22(2), pp.175-181.
  3. Akurugu, B.A., Chegbeleh, L.P. and Yidana, S.M. (2020). Characterisation of groundwater flow and recharge in crystalline basement rocks in the Talensi district, Northern Ghana. Journal of African Earth Sciences, 161, p.103665. https://doi.org/10.1016/j.jafrearsci.2019.103665
  4. Al-shabeeb, A.R.R. (2015). A modified analytical hierarchy process method to select sites for groundwater recharge in Jordan. Doctoral Dissertation. University of Leicester, United Kingdom.
  5. Alikhanov, B., Juliev, M., Alikhanova, S. and Mondal, I. (2021). Assessment of influencing factor method for delineation of groundwater potential zones with geospatial techniques. Case study of Bostanlik district, Uzbekistan. Groundwater for Sustainable Development, 12, p.100548. https://doi.org/10.1016/j.gsd.2021.100548
  6. Andualem, T.G. and Demeke, G.G. (2019). Groundwater potential assessment using GIS and remote sensing: A case study of Guna tana landscape, upper blue Nile Basin, Ethiopia. Journal of Hydrology: Regional Studies, 24, p.100610. https://doi.org/10.1016/j.ejrh.2019.100610
  7. Argaz, A., Ouahman, B., Darkaoui, A., Bikhtar, H., Yabsa, K. and Laghzal, A. (2019). Application of remote sensing techniques and GIS-multicriteria decision analysis for groundwater potential mapping in souss watershed, Morocco. Journal of Materials and Environmental Science, 10(5), pp.411-421.
  8. Badamasi, S., Sawa, B.A. and Garba, M.L. (2016). Groundwater potential zones mapping using remote sensing and geographic information system techniques (GIS) in Zaria, Kaduna State, Nigeria. American Academic Scientific Research Journal for Engineering, Technology, and Sciences, 24(1), pp.51-62.
  9. Balakrishnan, M. (2019). Groundwater potential zone mapping using geospatial techniques in Walayar watershed. International Journal of Engineering and Advanced Technology, 9(1), pp.1157-1161.
  10. Berhanu, K.G. and Hatiye, S.D. (2020). Identification of groundwater potential zones using proxy data: Case study of Megech watershed, Ethiopia. Journal of Hydrology: Regional Studies, 28, p.100676. https://doi.org/10.1016/j.ejrh.2020.100676
  11. Çelik, R. (2019). Evaluation of groundwater potential by GIS-based multicriteria decision making as a spatial prediction tool: Case study in the Tigris River Batman-Hasankeyf Sub-Basin, Turkey. Water, 11(12), p.2630. https://doi.org/10.3390/w11122630
  12. Desert Research Institute. (2016). WASH capacity building, action research & information dissemination in developing countries. Final Report: UNICEF Water in Selected Health Care Facilities Project and Communities Submitted to UNICEF Liberia. USA : The Desert Research Institute
  13. Dinesan, V.P., Gopinath, G. and Ashitha, M.K. (2015). Application of geoinformatics for the delineation of groundwater prospects zones-a case study for Melattur Grama Panchayat in Kerala, India. Aquatic Procedia, 4, pp.1389-1396.
  14. Duan, H., Deng, Z., Deng, F. and Wang, D. (2016). Assessment of groundwater potential based on multicriteria decision making model and decision tree algorithms. Mathematical Problems in Engineering, 2016, 2064575. https://doi.org/10.1155/2016/2064575
  15. FAO/UNESCO. (2003). The Digital Soil Map of the World. [Online]. Available at: https://www.fao.org/land-water/land/land-governance/land-resources-planning-toolbox/category/details/en/c/1026564/ (Accessed 10 December 2021)
  16. Goepel, K.D. (2013). Implementing the analytic hierarchy process as a standard method for multi-criteria decision making in corporate enterprises–a new AHP excel template with multiple inputs. In: Proceedings of the International Symposium on the Analytic Hierarchy Process, 2(10), pp. 1-10). Kuala Lumpur, Malaysia: Creative Decisions Foundation Kuala Lumpur.
  17. Joint Monitoring Report WHO UNICEF. (2017). Annual Joint Monitoring Report. [Online]. Available at: https://washdata.org/reports (Accessed 21 September 2021)
  18. Kaur, L., Rishi, M.S., Singh, G. and Thakur, S.N. (2020). Groundwater potential assessment of an alluvial aquifer in Yamuna sub-basin (Panipat region) using remote sensing and GIS techniques in conjunction with analytical hierarchy process (AHP) and catastrophe theory (CT). Ecological Indicators, 110, p.105850. https://doi.org/10.1016/j.ecolind.2019.105850
  19. León-Tavares, J., Roujean, J.L., Smets, B., Wolters, E., Toté, C. and Swinnen, E. (2021). Correction of directional effects in vegetation NDVI time-series. Remote Sensing, 13(6), p.1130.
  20. Mokadem, N., Boughariou, E., Mudarra, M., Brahim, F.B., Andreo, B., Hamed, Y. and Bouri, S. (2018). Mapping potential zones for groundwater recharge and its evaluation in arid environments using a GIS approach: Case study of North Gafsa Basin (Central Tunisia). Journal of African Earth Sciences, 141, pp.107-117.
  21. Murasingh, S., Jha, R. and Adamala, S. (2018). Geospatial technique for delineation of groundwater potential zones in mine and dense forest area using weighted index overlay technique. Groundwater for sustainable development, 7, pp.387-399.
  22. Murmu, P., Kumar, M., Lal, D., Sonker, I. and Singh, S.K. (2019). Delineation of groundwater potential zones using geospatial techniques and analytical hierarchy process in Dumka district, Jharkhand, India. Groundwater for Sustainable Development, 9, p.100239.
  23. Omran, A.F.A. (2013). Application of GIS and Remote Sensing for water resource management in arid area - Wadi Dahab Basin - South Eastern Sinai-Egypt (Case-study). Doctoral dissertation. Universitätsbibliothek Tübingen.
  24. Patra, S., Mishra, P. and Mahapatra, S.C. (2018). Delineation of groundwater potential zone for sustainable development: A case study from Ganga Alluvial Plain covering Hooghly district of India using remote sensing, geographic information system and analytic hierarchy process. Journal of Cleaner Production, 172, pp.2485-2502.
  25. Reddy, Y.V.K., Lakshmi, D.S.V. (2018). Identification of Groundwater Potential Zones Using Gis and Remote Sensing. Int. J. Pure Appl. Math. 119, 3195–3210.
  26. Sing, N.M.M.N., Halim, M.A., Hashim, N.I., Hashim, N., Naharudin, N. and Rasam, A.R.A., (2020) Identification of groundwater potential zones in Langkawi through Remote Sensing and Geographic Information System (GIS) techniques. In: 2020 IEEE 10th International Conference on System Engineering and Technology (ICSET), pp.26-31. IEEE.
  27. Singh, L.K., Jha, M.K. and Chowdary, V.M. (2018). Assessing the accuracy of GIS-based multi-criteria decision analysis approaches for mapping groundwater potential. Ecological Indicators, 91, pp.24-37.
  28. Siqueira, L., Freiman, F.P., Silva, J.R. (2018). Groundwater Potential Zone Identification in the Crystalline Basement Rock Terrain of Liberia Using Integrated Remote Sensing and GIS. Revista Brasileira de Geografia Física,11, pp. 988–994.
  29. Solomon, S. and Quiel, F. (2003). Integration of remote sensing and GIS for groundwater assessment in Eritrea. In Proc of the European Association of Remote Sensing Laboratories Conf (pp. 633-640).
  30. Suganthi, S., Elango, L. and Subramanian, S.K. (2013). Groundwater potential zonation by Remote Sensing and GIS techniques and its relation to the Groundwater level in the Coastal part of the Arani and Koratalai River Basin, Southern India. Earth Sciences Research Journal, 17(2), pp.87-95.
  31. UNICEF Liberia. (2017). UNICEF Liberia Report. 2020 IEEE 10th Int. Conf. Syst. Eng. Technol. ICSET 2020 [Online]. Available at: https://www.unicef.org/liberia/water-sanitation-and-hygiene (Accessed 4 January 2021).
  32. United Nations. (2015). The United Nations world water development report 2015: water for a sustainable world [Online]. Available at: https://unesdoc.unesco.org/ark:/48223/pf0000231823 (Accessed 14 January 2021)
  33. USDA-FAS State Department. (1951). Reconnaissance Soil Survey of Liberia. [Online]. Available at: https://naldc.nal.usda.gov/download/CAT87210307/PDF (Accessed 30 January 2022)
  34. USGS. (1971). The Monrovia Quadrangle. [Online]. Available at: https://pubs.usgs.gov/of/1974/0305/report.pdf (Accessed 12 December 2021)
  35. USGS. (2014). EarthExplorer Remote Sensing Data. [Online]. Available at: https://earthexplorer.usgs.gov/ (Accessed 8 January 2022).
  36. Veldkamp, W.J. (1980). Soil survey and land evaluation in the Mano River Union [Online]. Available at: https://edepot.wur.nl/487414 (Accessed 8 January 2021)
  37. Waikar, M.L. and Nilawar, A.P. (2014). Identification of groundwater potential zone using remote sensing and GIS technique. International Journal of Innovative Research in Science, Engineering and Technology, 3(5), pp.12163-12174.
  38. Yachiyo Engineering Co. Liberia. (2010). The Master Plan Study On Urban Facilities Restoration And Improvement In Monrovia In The Republic Of Liberia. Groundwater Development Plan In Paynesville Area - Final Report. [Online]. Available at: https://openjicareport.jica.go.ip>pdf (Accessed 19 October 2022)