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Identification of Potential Groundwater Recharge Sites in a Semi-arid Region of Pakistan Using Saaty´s Analytical Hierarchical Process (AHP)
Corresponding Author(s) : Muhammad Suliman
Geomatics and Environmental Engineering,
Vol. 16 No. 1 (2022): Geomatics and Environmental Engineering
Abstract
Groundwater is a precious source of fresh water and a major component of the entire water supply. Both water quality and quantity could be satisfied by evaluating the groundwater potential sites (GWPS). This paper analyzes the ground-water potentials in a semi-arid region of Khyber Pakhtunkhwa, Pakistan. It describes a standard methodology to identify and map GWPS using integrated Geographical Information System (GIS) and remote sensing (RS) methods. Eight parameters including elevation, slope, drainage density, lineaments density, soil, geology, land use/land cover and rainfall were integrated to explore areas with groundwater holding capability. GWPS were delineated through subjective weights assigned after coupling various thematic layers using Saaty´s Analytical Hierarchical Process (AHP). The modelled GWPS were cross-checked with tube wells data. The result indicates that the central part of the study area has good potential for groundwater reserves/exploitation, where the factors i.e. moderate to high drainage density, sedimentary sequence of alluvial plain, low elevation etc. discern the central portion of the study area as a suitable site for groundwater. This study suggests that the applied method proves to be very significant and reliable tool for timely assessment of quality assured evaluation of groundwater resources. This study could be a systematic guide for future investigations for water related explorations, especially in semi-arid environments.
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- Srivastava P.K., Bhattacharya A.K.: Groundwater assessment through an integrated approach using remote sensing, GIS and resistivity techniques: a case study from a hard rock terrain. International Journal of Remote Sensing, vol. 27, no. 20, 2006, pp. 4599–4620. https://doi.org/10.1080/01431160600554983.
- Al-Djazouli M.O., Elmorabiti K., Rahimi A., Amellah O., Fadil O.A.M.: Delineating of groundwater potential zones based on remote sensing, GIS and analytical hierarchical process: a case of Waddai, eastern Chad. GeoJournal, vol. 86, 2021, pp. 1881–1894. https://doi.org/10.1007/s10708-020-10160-0.
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- Aneesh R., Deka P.C.: Groundwater potential recharge zonation of Bengaluru ur- ban district – a GIS based analytic hierarchy process (AHP) technique approach. International Advanced Research Journal in Science, Engineering and Technology, vol. 2, no. 6, 2015, pp. 129–136.
- Harinarayana P., Gopalakrishna G., Balasubramanian A.: Remote sensing data for groundwater development and management in Keralapura watersheds of Cauvery basin, Karnataka, India. The Indian Mineralogist, vol. 34, no. 2, 2000, pp. 11–17.
- Kahlown M.A., Majeed A.: Water-resources situation in Pakistan: challenges and future strategies. [in:] Water Resources in the South: present scenario and future prospects, COMSATS, 2003, pp. 21–39.
- Abdullah A., Akhir J.M., Abdullah I.: Automatic mapping of lineaments using shaded relief images derived from digital elevation model (DEMs) in the Maran–Sungi Lembing area, Malaysia. Electronic Journal of Geotechnical Engineering, vol. 16, no. 6, 2010, pp. 949–958.
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- UNESCO: Water in a Changing World (WWDR-3): the 3rd United Nations World Water Development Report. UNESCO World Water Assessment Programme, 2009, http://www.unesco.org/new/en/natural-sciences/environment/water/wwap/wwdr/wwdr3-2009/ [access: 7.06.2019].
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- Ullah S., Khan M.R., Shah N.A., Shah S.A., Majid M., Farooq M.A.: Ethnomedicinal plant use value in the Lakki Marwat District of Pakistan. Journal of ethnopharmacology, vol. 158, 2014, pp. 412–422. https://doi.org/10.1016/j.jep.2014.09.048.
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- Tweed S.O., Leblanc M., Webb J.A., Lubczynski M.W.: Remote sensing and GIS for mapping groundwater recharge and discharge areas in salinity prone catchments, southeastern Australia. Hydrogeology Journal, vol. 15, no. 1, 2007, pp. 75–96. https://doi.org/10.1007/s10040-006-0129-x.
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- Sujatha E.R., Sridhar V.: Landslide susceptibility analysis: a logistic regression model case study in Coonoor, India. Hydrology, vol. 8, no. 1, 2021, 41. https://doi.org/10.3390/hydrology8010041.
- Arshad A., Zhang Z., Zhang W., Dilawar A.: Mapping favorable groundwater potential recharge zones using a GIS-based analytical hierarchical process and probability frequency ratio model: A case study from an agro-urban region of Pakistan. Geoscience Frontiers, vol. 11, no. 5, 2020, pp. 1805–1819. https://doi.org/10.1016/j.gsf.2019.12.013.
- Baker C., Lawrence R., Montagne C., Patten D.: Mapping wetlands and riparian areas using Landsat ETM+ imagery and decision-tree-based models. Wetlands, vol. 26, no. 2, 2006, pp. 465–474. https://doi.org/10.1672/0277-5212(2006)26[465:MWARAU]2.0.CO;2.
- Saaty T.L.: How to make a decision: the analytic hierarchy process. European Journal of Operational Research, vol. 48, no. 1, 1990, pp. 9–26. https://doi.org/10.1016/0377-2217(90)90057-I.
- Mukul M., Srivastava V., Jade S., Mukul M.: Uncertainties in the shuttle radar topography mission (SRTM) Heights: Insights from the Indian Himalaya and Peninsula. Scientific Reports, vol. 7, no. 1, 2017, 41672. https://doi.org/10.1038/srep41672.
- Magesh N.S., Chandrasekar N., Soundranayagam J.P.: Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques. Geoscience Frontiers, vol. 3, no. 2, 2012, pp. 189–196. https://doi.org/10.1016/j.gsf.2011.10.007.
- Jenks G.F.: The data model concept in statistical mapping. [in:] Frenzel K. (ed.), International Yearbook of Cartography, vol. 7, George Philip, 1967, pp. 186–190.
References
Srivastava P.K., Bhattacharya A.K.: Groundwater assessment through an integrated approach using remote sensing, GIS and resistivity techniques: a case study from a hard rock terrain. International Journal of Remote Sensing, vol. 27, no. 20, 2006, pp. 4599–4620. https://doi.org/10.1080/01431160600554983.
Al-Djazouli M.O., Elmorabiti K., Rahimi A., Amellah O., Fadil O.A.M.: Delineating of groundwater potential zones based on remote sensing, GIS and analytical hierarchical process: a case of Waddai, eastern Chad. GeoJournal, vol. 86, 2021, pp. 1881–1894. https://doi.org/10.1007/s10708-020-10160-0.
Singh P., Singh A., Vijhani A.: Groundwater potential zone mapping approach in Chandraprabha Basin UP using remote sensing & GIS Technology. [in:] 15th Esri India User Conference, Delhi, 2014, UCP0031. https://www.esri.in/~/media/esri-india/files/pdfs/events/uc2014/proceedings/papers/UCP0031.pdf?la=en.
Hashemi H., Uvo C.B., Berndtsson R.: Coupled modeling approach to assess climate change impacts on groundwater recharge and adaptation in arid areas. Hydrology & Earth System Sciences, vol. 19, no. 10, 2015, pp. 4165–4181. https://doi.org/10.5194/hess-19-4165-2015.
Aneesh R., Deka P.C.: Groundwater potential recharge zonation of Bengaluru ur- ban district – a GIS based analytic hierarchy process (AHP) technique approach. International Advanced Research Journal in Science, Engineering and Technology, vol. 2, no. 6, 2015, pp. 129–136.
Harinarayana P., Gopalakrishna G., Balasubramanian A.: Remote sensing data for groundwater development and management in Keralapura watersheds of Cauvery basin, Karnataka, India. The Indian Mineralogist, vol. 34, no. 2, 2000, pp. 11–17.
Kahlown M.A., Majeed A.: Water-resources situation in Pakistan: challenges and future strategies. [in:] Water Resources in the South: present scenario and future prospects, COMSATS, 2003, pp. 21–39.
Abdullah A., Akhir J.M., Abdullah I.: Automatic mapping of lineaments using shaded relief images derived from digital elevation model (DEMs) in the Maran–Sungi Lembing area, Malaysia. Electronic Journal of Geotechnical Engineering, vol. 16, no. 6, 2010, pp. 949–958.
Adiat K., Nawawi M., Abdullah K.: Assessing the accuracy of GIS-based elementary multi criteria decision analysis as a spatial prediction tool – a case of predicting potential zones of sustainable groundwater resources. Journal of Hydrology, vol. 440–441, 2012, pp. 75–89. https://doi.org/10.1016/j.jhydrol.2012.03.028.
Jha M.K., Chowdary V., Chowdhury A.: Groundwater assessment in Salboni Block, West Bengal (India) using remote sensing, geographical information system and multi-criteria decision analysis techniques. Hydrogeology Journal, vol. 18, no. 7, 2010, pp. 1713–1728. https://doi.org/10.1007/s10040-010-0631-z.
Saranya T., Saravanan S.: Groundwater potential zone mapping using analytical hierarchy process (AHP) and GIS for Kancheepuram District, Tamilnadu, In- dia. Modeling Earth Systems and Environment, vol. 6, 2020, pp. 1105–1122. https://doi.org/10.1007/s40808-020-00744-7.
Chowdhury A., Jha M.K., Chowdary V.: Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS, GIS and MCDM techniques. Environmental Earth Sciences, vol. 59, no. 6, 2010, 1209. https://doi.org/10.1007/s12665-009-0110-9.
Majeed Z., Piracha A.: Water conservation of Pakistan’s agricultural, municipal and industrial water. International Journal of Water Resources and Arid Environments, vol. 1, no. 3, 2011, pp. 232–238. https://doi.org/10.1007/s10661-014-3876-5.
Farid A., Khalid P., Jadoon K.Z., Jouini M.S.: The depositional setting of the Late Quaternary sedimentary fill in southern Bannu basin, Northwest Himalayan fold and thrust belt, Pakistan. Environmental Monitoring and Assessment, vol. 186, no. 10, 2014, pp. 6587–6604. https://doi.org/10.1007/s10661-014-3876-5.
UNESCO: Water in a Changing World (WWDR-3): the 3rd United Nations World Water Development Report. UNESCO World Water Assessment Programme, 2009, http://www.unesco.org/new/en/natural-sciences/environment/water/wwap/wwdr/wwdr3-2009/ [access: 7.06.2019].
Ahmad N., Khan M.R.: Evaluation of a distinct sub-play for enhanced exploration in an emerging petroleum province, Bannu-Kohat sub-basin, Pakistan. [in:] AAPG International Conference and Exhibition, Milan, Italy, October 23–26, 2011. https://www.searchanddiscovery.com/documents/2012/10391ahmad/ndx_ahmad.
Ullah S., Khan M.R., Shah N.A., Shah S.A., Majid M., Farooq M.A.: Ethnomedicinal plant use value in the Lakki Marwat District of Pakistan. Journal of ethnopharmacology, vol. 158, 2014, pp. 412–422. https://doi.org/10.1016/j.jep.2014.09.048.
Saeed T.U., Khan D.: Assessment and conservation of groundwater quality: A challenge for agriculture. British Journal of Applied Science & Technology, vol. 4, no. 8, 2014, pp. 1256–1272. https://doi.org/10.9734/BJAST/2014/6353.
Tweed S.O., Leblanc M., Webb J.A., Lubczynski M.W.: Remote sensing and GIS for mapping groundwater recharge and discharge areas in salinity prone catchments, southeastern Australia. Hydrogeology Journal, vol. 15, no. 1, 2007, pp. 75–96. https://doi.org/10.1007/s10040-006-0129-x.
Singh K.P., Basant A., Malik A., Jain G.: Artificial neural network modeling of the river water quality – a case study. Ecological Modelling, vol. 220, no. 6, 2009, pp. 888–895. https://doi.org/10.1016/j.ecolmodel.2009.01.004.
Yeh H.F., Lee C.H., Hsu, K.C., Chang P.H.: GIS for the assessment of the groundwater recharge potential zone. Environmental Geology, vol. 5, no. 1, 2009, pp. 185–195. https://doi.org/10.1007/s00254-008-1504-9.
Shekhar S., Pandey A.C.: Delineation of groundwater potential zone in hard rock terrain of India using remote sensing, geographical information system (GIS) and analytic hierarchy process (AHP) techniques. Geocarto International, vol. 30, no. 4, 2015, pp. 402–421. https://doi.org/10.1080/10106049.2014.894584.
Pinto D., Shrestha S., Babel M.S., Ninsawat S.: Delineation of groundwater potential zones in the Comoro watershed, Timor Leste using GIS, remote sensing and analytic hierarchy process (AHP) technique. Applied Water Science, vol. 7, no. 1, 2017, pp. 503–519. https://doi.org/10.1007/s13201-015-0270-6.
Sujatha E.R., Sridhar V.: Landslide susceptibility analysis: a logistic regression model case study in Coonoor, India. Hydrology, vol. 8, no. 1, 2021, 41. https://doi.org/10.3390/hydrology8010041.
Arshad A., Zhang Z., Zhang W., Dilawar A.: Mapping favorable groundwater potential recharge zones using a GIS-based analytical hierarchical process and probability frequency ratio model: A case study from an agro-urban region of Pakistan. Geoscience Frontiers, vol. 11, no. 5, 2020, pp. 1805–1819. https://doi.org/10.1016/j.gsf.2019.12.013.
Baker C., Lawrence R., Montagne C., Patten D.: Mapping wetlands and riparian areas using Landsat ETM+ imagery and decision-tree-based models. Wetlands, vol. 26, no. 2, 2006, pp. 465–474. https://doi.org/10.1672/0277-5212(2006)26[465:MWARAU]2.0.CO;2.
Saaty T.L.: How to make a decision: the analytic hierarchy process. European Journal of Operational Research, vol. 48, no. 1, 1990, pp. 9–26. https://doi.org/10.1016/0377-2217(90)90057-I.
Mukul M., Srivastava V., Jade S., Mukul M.: Uncertainties in the shuttle radar topography mission (SRTM) Heights: Insights from the Indian Himalaya and Peninsula. Scientific Reports, vol. 7, no. 1, 2017, 41672. https://doi.org/10.1038/srep41672.
Magesh N.S., Chandrasekar N., Soundranayagam J.P.: Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques. Geoscience Frontiers, vol. 3, no. 2, 2012, pp. 189–196. https://doi.org/10.1016/j.gsf.2011.10.007.
Jenks G.F.: The data model concept in statistical mapping. [in:] Frenzel K. (ed.), International Yearbook of Cartography, vol. 7, George Philip, 1967, pp. 186–190.