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Application of GIS-Based Evidential Belief Function Model to Regional Groundwater Recharge Potential Zones Mapping in Hardrock Geologic Terrain

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Abstract

The evidential belief function – Dempster-Shafer theory (EBF-DST) model was applied and validated for groundwater recharge potential zoning in the hard-rock geologic terrain, southwestern Nigeria, using geographic information systems (GIS). Data about related factors, including satellite imagery, climate and geology were collected and input into a spatial database. In addition, groundwater well yield data inventory of the area were collected from 78 well locations. The groundwater well yield data were partitioned into two data sets, using partitioning criterion ratio of 70 to 30 for training and validation of the model. By using the constructed spatial database, six groundwater recharge conditioning factors such as slope, drainage density, lineament density, lineament intersection density, lithology and rainfall were extracted. The relationships between the well locations and the factors were identified and quantified by using the EBF-DST model. Four belief function series were calculated: belief (Bel), disbelief (Dis), uncertainty (Unc), and plausibility (Pls). The integrated belief function was used to produce the groundwater recharge potential prediction index (GRPPI) map. Furthermore, to compare the performance of the EBF-DST result, multi-criteria decision analysis - analytic hierarchy process (MCDA-AHP) model was applied. The success-rate and prediction-rate curves were computed to estimate the efficiency of the proposed EBF-DST model compared to the MCDA-AHP model. The validation results demonstrated that the success-rate for EBF-DST and MCDA-AHP models were 89 and 82 %, respectively. The area under the curve (AUC) of prediction-rate for both EBF-DST and MCDA-AHP models were calculated as 89 and 78 %, respectively. The outputs accomplished from the current research proved the efficacy of EBF-DST model in groundwater recharge potential zones mapping.

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References

  • Adiat KAN, Nawawi MNM, Abdullah K (2012) 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. J Hydrol 440:75–89. doi:10.1016/j.jhydrol.2012.03.028

    Article  Google Scholar 

  • Adiat KAN, Nawawi MNM, Abdullah K (2013) Application of multicriteria decision analysis to geoelectric and geologic parameters for spatial prediction of groundwater resources potential and aquifer evaluation pure. Appl Geophys 170:453–471. doi:10.1007/s00024-012-0501-9

    Article  Google Scholar 

  • Akgun A, Sezer EA, Nefeslioglu HA, Gokceoglu C, Pradhan B (2012) An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm. Comput Geosci 38(1):23–34

    Article  Google Scholar 

  • Al-Abadi AM (2015) The application of Dempster-Shafer theory of evidence for assessing groundwater vulnerability at Galal Badra basin, Wasit governorate, east of Iraq. Appl Water Sci. doi:10.1007/s13201-015-0342-7

    Google Scholar 

  • Al-Saud M (2008) Using ASTER images to analyze geologic linear features in Wadi Aurnah basin, western Saudi Arabia. Open Remote Sensing techniques. Hydrogeol J 18:1481–1495

    Article  Google Scholar 

  • Al-Saud M (2010) Mapping potential areas for groundwater storage in Wadi Aurnah Basin, western Arabian Peninsula, using remote sensing and geographic information system techniques. Hydrogeol J 18:1481–1495

    Article  Google Scholar 

  • Althuwaynee OF, Pradhan B, Lee S (2012) Application of an evidential belief function model in landslide susceptibility mapping. Comput Geosci 44:120–135. doi:10.1016/j.cageo.2012.03.003

    Article  Google Scholar 

  • Awasthi A, Chautan SS (2011) Using AHP and Dempster-Shafer theory for evaluating sustainable transport solution. Environ Model Softw 26:781–796

    Article  Google Scholar 

  • Ayazi MH, Pirasteh S, Arvin AKP, Pradhan B, Nikouravan B, Mansor S (2010) Disasters and risk reduction in groundwater: Zagros mountain southwest Iran using geo-informatics techniques. Dis Adv 3(1)

  • Bala AN, Ike EC (2001) The aquifer of the crystalline basement rocks in Gusau area, North-western Nigeria. J Min Geol 37(2):177–184

    Google Scholar 

  • Carranza EJM, Castro OT (2006) Predicting lahar-inundation zones: case study in West Mount Pinatubo, Philippines. Nat Hazards 37(3):331–372

    Article  Google Scholar 

  • Carranza EJM, Hale M (2002) Evidential belief functions for data-driven geologically constrained mapping of gold potential, Baguio district, Philippines. Ore Geol Rev 22(1):117–132

    Google Scholar 

  • Carranza EJM, Woldai T, Chikambwe EM (2005) Application of data-driven evidential belief functions to prospectivity mapping for aquamarine-bearing pegmatites, Lundazi District, Zambia. Nat Resour Res 14 (1). doi: 10.1007/s11053-005-4678-9

  • Cervi F, Berti M, Borgatti L, Ronchetti F, Manenti F, Corsini A (2010) Comparing predictive capability of statistical and deterministic methods for landslide susceptibility mapping: a case study in the northern Apennines (Reggio Emilia Province, Italy). Landslides 7(4):433–444

    Article  Google Scholar 

  • Chandra S, Chand R, Rao VA, Singh VS, Jain SC (2004) Estimation of natural recharge and its dependency on sub-surface geoelectric parameters. J Hydrol. doi:10.1016/j.jhydrol.2004.04.001

    Google Scholar 

  • Charon JE (1974) Hydrogeological applications of ERTS satellite imagery. In: Proc UN/FAO Regional Seminar on Remote Sensing of Earth Resources and Environment, Cairo. Commonwealth Science Council, 439–456

  • Chowdhury A, Jha MK, Chowdary VM, Mal BC (2009) Integrated remote sensing and GIS‐based approach for assessing groundwater. Int J Remote Sens 30(1):231–250

    Article  Google Scholar 

  • Dan-Hassan MA, Olorunfemi MO (1999) Hydro-geophysical investigation of a basement terrain in the north central part of Kaduna State. Niger J Min Geol 35(2):189–206

    Google Scholar 

  • Dempster AP (1967) Upper and lower probabilities induced by a multivalued mapping. Ann Math Stat 38:325–339

    Article  Google Scholar 

  • Dempster AP (1968) Generalization of Bayesian inference. J R Stat Soc Ser B 30:205–247

    Google Scholar 

  • Dempster A (2008) Upper and lower probabilities induced by a multivalued mapping. In: Yager R, Liu L, Dempster AP, Shafer G (eds) Classic works of the Dempster-Shafer theory of belief functions. Springer, Berlin, Heidelberg, pp 57–72 (Chapter 3)

    Chapter  Google Scholar 

  • Edet AE, Okereke CS (1996) Assessment of hydrogeological conditions in basement aquifers of the Precambrian Oban Massif, Southwestern Nigeria. J Appl Geophys 36:195–204

    Article  Google Scholar 

  • Edet AE, Okereke CS (1997) Assessment of hydrogeological conditions in basement aquifers of the Precambrian Oban massif, southeastern Nigeria. J Appl Geophys 36:195–204

    Article  Google Scholar 

  • Edet AE, Okereke CS, Teme SC, Esu EO (1998) Application of remote sensing data to groundwater exploration: a case study of the cross-river state, Southeastern Nigeria. Hydrogeol J 6:394–404

    Article  Google Scholar 

  • Ettazarini S, El - Mahmouhi N (2004) Vulnerability mapping of the Turonian limestone aquifer in the Phosphates Plateau (Morocco). Environ Geol 46:113–117. doi:10.1007/s00254-004-1022-3

    Google Scholar 

  • European Commission (1995) Soil terrain database land management and natural hazards and units. IES and JRC, European Commission Brussels

    Google Scholar 

  • Fitts CR (2002) Groundwater science. Academic, San Diego

    Google Scholar 

  • Freeze RA, Cherry JA (1979) Groundwater. Prentice-Hall, Englewood.Cliffs fitts CR (2002) Groundwater science. Academic, San Diego 51–57

  • Garfì M, Tondelli S, Bonoli A (2009) Multi-Criteria decision analysis for waste management in Saharawi Refugee Camps. Waste Manag 29(10):2729–2739

    Article  Google Scholar 

  • Gontia NK, Patil PY (2012) Assessment of groundwater recharge through rainfall and water harvesting structures in Jamka Microwatershed using remote sensing and GIS. J Indian Soc Remote Sens 40(4):639–648. doi:10.1007/s12524-011-0176-1

    Article  Google Scholar 

  • Greenbaum D (1992) Structural influences on the occurrence of groundwater in SE Zimbabwe. Geol Soci London Special Pub 66:77–85

    Article  Google Scholar 

  • Jha MK, Chowdhury A, Chowdary VM, Peiffer S (2007) Groundwater management and development by integrated remote sensing and geographic information systems: prospects and constraints. Water Resour Manag 21:427–467

    Article  Google Scholar 

  • Jha MK, Chowdary VM, Chowdhury A (2010) Groundwater assessment in Salboni block, West Bengal (India) using remote sensing, geographical information system and multi-criteria decision analysis techniques. Hydrogeol J 23–30

  • Jone HA, Hockey RD (1964) The geology of part of south-western Nigeria. Geol Surv Nigeria Bull 31, 87p

  • Krishnamurthy J, Kumar NV, Jayaraman V, Manivel M (1996) An approach to demarcate groundwater potential zones through remote sensing and a geographic information system. Int J Remote Sens 17(10):1867–1884

    Article  Google Scholar 

  • Kumar CP (2000) Groundwater assessment methodology. 21: National Institute of Hydrology

  • Kumar CP, Seethapathi PV (2002) Assessment of natural ground water recharge in upper Ganga Canal command area. J Appl Hydrol 15: (4)13–20. Online Internet.From http://www.angelfire.com/nh//publication/ugcm.pdf

  • Lee S, Hwang J, Park I (2012) Application of data – driven evidential belief functions to landslide susceptibility mapping in Jinbu Korea, CATENA, 100:15–30

  • Machiwal D, Jha MK (2014) Characterizing rainfall-groundwater dynamics in a hard-rock aquifer system using time series, geographic information system and geostatistical modelling. Hydrol Process 28:2824–2843

    Article  Google Scholar 

  • Madan KJ, Chowdary V M, Chowdhury A (2010) Groundwater assessment in Salboni Block, West Bengal (India) using Remote Sensing, Geographical Information System and Multi-criteria Decision Analysis Techniques. Hydrogeol J 23–30

  • Magesh NS, Chandrasekar N, Soundranayagam JP (2012) Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques. Geosci Front 3(2):189–196

    Article  Google Scholar 

  • Mahmoud SH, Alazba AA, Amin MT (2014) Identification of potential sites for groundwater recharge using a GIS-based decision support system in Jazan Region-Saudi Arabia. Water Resour Manag 28:3319–3340. doi:10.1007/s11269-014-0681-4

    Article  Google Scholar 

  • Manap MA, Nampak H, Pradhan B, Lee S, Sulaiman WNA, Ramli MF (2012) Application of probabilistic-based frequency ratio model in groundwater potential mapping using remote sensing data and GIS. Arab J Geosci 7:711–724

  • Manap MA, Sulaiman WNA, Ramli MF, Pradhan B, Surip N (2013) Aknowledge-driven GIS modeling technique for groundwater potential mapping at the Upper Langat Basin, Malaysia. Arab J Geosci 6:1621–1637

    Article  Google Scholar 

  • Mogaji KA, Lim HS, Abdullah K (2013b) Modeling groundwater vulnerability prediction using geographic information system (GIS)-based ordered weighted average (OWA) method and DRASTIC model theory hybrid approach. Arab J Geosci 1–21

  • Mogaji KA, Lim HS, Abdullah K (2014) Regional prediction of groundwater potential mapping in a multifaceted geology terrain using GIS-based Demspter–Shafer model. Arab J Geosci. doi:10.1007/s12517-014-1391-1

    Google Scholar 

  • Mogaji KA, Lim H, Abdullah K (2015) Modeling of groundwater recharge using a multiple linear regression (MLR) recharge model developed from geophysical parameters: a case of groundwater resources management. Environ Earth Sci 73:1217–1230

    Article  Google Scholar 

  • Mohammady M, Pourghasemi HR, Pradhan B (2012) Landslide susceptibility mapping at golestan province, Iran: a comparison between frequency ratio, Dempster–Shafer, and weights-of-evidencemodels. J Asian Earth Sci 61:221–236

    Article  Google Scholar 

  • Moon WM (1990) Integration of geophysical and geological data using evidential belief function. IEEE Trans Geosci Remote Sens 28(4):711–720

    Article  Google Scholar 

  • Mukherjee S (1996) Targeting saline aquifer by remote sensing and geophysical methods in a part of Hamirpur_Kanpur, India. Hydro J 19:1867–1884

    Google Scholar 

  • Murthy KSR (2000) Groundwater potential in a semi-arid region of Andhra Pradesh: a GIS approach. Int J Remote Sens 21(9):1867–1884

    Article  Google Scholar 

  • Nampak H, Pradhan B, Manap MA (2014) Application of GIS based data driven evidential belief function model to predict groundwater potential zonation. J Hydrol 513:283–300

    Article  Google Scholar 

  • Neshat A, Pradhan B, Pirasteh S, Shafri HZM (2013) Estimating groundwater vulnerability to pollution using modified DRASTIC model in the Kerman agricultural area Iran. Environ Earth Sci. doi:10.1007/s12665-013-2690-7

    Google Scholar 

  • Nimmo JR, Healy RW, Stonestrom DA (2005) Aquifer recharge. In: Anderson MG, Bear J (eds) Encyclopedia of hydrological science, vol 4. Universiti Sains Malaysia, Chichester, pp 2229–2246

    Google Scholar 

  • Nolan BT, Healy RW, Taber PE, Perkins K, Hitt KJ, Wolock DM (2007) Factors influencing ground-water recharge in the eastern United States. J Hydrol 332(1–2):187. doi:10.1016/j.jhydrol.2006.06.029

    Article  Google Scholar 

  • Oh HJ, Kim YS, Choi JK, Lee S (2011) GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea. J Hydrol 399:158–172

    Article  Google Scholar 

  • Ozdemir A (2011) GIS-based groundwater spring potential mapping in the Sultan Mountains (Konya, Turkey) using frequency ratio, weights of evidence and logistic regression methods and their comparison. J Hydrol 411:290–308

    Article  Google Scholar 

  • Ozdemir A, Altural T (2013) A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey. J Asian Earth Sci 64:180–197

    Article  Google Scholar 

  • Park NW (2011) Application of Dempster–Shafer theory of evidence to GIS-based landslide susceptibility analysis. Environ Earth Sci 62:367–376. doi:10.1007/s12665-010-0531-5

    Article  Google Scholar 

  • Pourghasem HR, Davoodi MD, Rezaei M, Pradhan PB (2013) Groundwater spring potential mapping using bivariate statistical model and GIS in the Taleghan Watershed. Iran Arab J Geosci. doi:10.1007/s12517-013-1161-5

    Google Scholar 

  • Pourghasem HR, Seyed AN, Zohre SP (2014) Groundwater qanat potential mapping using frequency ratio and Shannon’s entropy models in the Moghan watershed. Iran Earth Sci Inform. doi:10.1007/s12145-014-0145-7

    Google Scholar 

  • Pourghasem HR, Yousef R, Najmeh SN, Omid R (2015) Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS. Earth Sci Inform. doi:10.1007/s12145-015-0220-8

    Google Scholar 

  • Pourghasemi HR, Moradi HR, Fatemi Aghda SM, Gokceoglu C, Pradhan B (2012) GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran, Iran). Arab J Geosci 7(5):1857–1878

    Article  Google Scholar 

  • Pourghasemi HR, Moradi HR, Fatemi Aghda SM, Gokceoglu C, Pradhan B (2013) GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran, Iran). Arab J Geosci. doi:10.1007/s12517-012-0825-x

    Google Scholar 

  • Pradhan B (2009) Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques. Cent Eur J Geosci 1(1):120–129

    Google Scholar 

  • Pradhan B (2013) A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS. Comput Geosci 51:350–365

    Article  Google Scholar 

  • Pradhan B, Lee S, Buchroithner MF (2010) Remote sensing and GIS based landslide susceptibility analysis and its cross-validation in three test areas using a frequency ratio model. Photogramm Fernerkun 1:17–32. doi:10.1127/1432-8364/2010/0037

    Article  Google Scholar 

  • Prasad RK, Mondal NC, Banerjec P, Nandakumar MV, Singh VS (2008) Deciphering potential of groundwater zones in hardrock through application of GIS. Environ Geol 55:467–475

    Article  Google Scholar 

  • Rahaman MA (1988) Recent advances in the study of the basement complex of Nigeria Precambrian Geology of Nigeria. Geol. Surv. Nig 11–41

  • Rahaman MA, Ocan O (1978) On the relationships in the Precambrian Magmatic Gneiss of Nigeria. J Min Geol 15:23–32

    Google Scholar 

  • Saaty TL (1980) The analytic hierarchy process: planning, priority setting, resource allocation. McGraw-Hill, New York

    Google Scholar 

  • Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48:9–26

    Article  Google Scholar 

  • Saaty TL, Vargas GL (1991) Prediction, projection and forecasting Kluwer, Dordrecht

  • Satpathy BN, Kanungo BN (1976) Groundwater exploration in hard rock terrain- A case study. Geophys Prospect 24(4):725–763

    Article  Google Scholar 

  • Scanlon BR, Healy RW, Cook PG (2002) Choosing appropriate techniques for quantifying groundwater recharge. Hydrogeol J 10:18–39. doi:10.1007/s10040-001-0176-2

    Article  Google Scholar 

  • Sener E, Davra A, Ozcelik M (2005) An integration of GIS and remote sensing in groundwater investigation: A case study in Bunduc. Turk, Hydrogeol 13(5):836–839

  • Shafer GA (1976) Mathematical theory of evidence. Princeton University Press, Princeton, pp 1–24

    Google Scholar 

  • Sharma ML (1986) Measurement and prediction of natural groundwater recharge an overview. J Hydrol 25:86–94

    Google Scholar 

  • Shuy BE, Tan SBS, Chua CHL (2007) Regression method for estimating rainfall at unconfined sandy aquifers with an equatorial climate. Hydrol Process 21:3514–3526. doi:10.1002/HYP.6552

    Article  Google Scholar 

  • Simmers (1998) Groundwater recharge: an overview of estimation ‘problems’ and recent developments. Geol Soc Lond, Spec Publ 130:107–115. doi:10.1144/GSL.SP.1998.130.01.10

    Article  Google Scholar 

  • Thirumalaivasan D, Karmegam M, Venugopal K (2003) AHP-DRASTIC: software for specific aquifer vulnerability assessment using DRASTIC model and GIS. Environ Model Softw 18:645–656

    Article  Google Scholar 

  • Vahidnia MH, Alesheikh A, Alimohammadi A, Bassiri A (2008) Fuzzy analytical hierarchy process in GIS application. Int Arch Photogramm Remote Sens Spat Inf Sci 37(B2):593–596

    Google Scholar 

  • Wright DF, Bonham-Carter GF (1996) VHMS favourability mapping with GIS-based integration models, Chisel Lake–Anderson Lake area. In EXTECH I, a multidisciplinary approach to massive Sulphide research in the rusty Lake-Snow Lake Greenstone Belts, Manitoba, Geological Survey of Canada. Bulletin 426, 339–376

  • Zhou L, Chen Y (2014) Exploring the potential of community-based grassland management in Yanchi County of Ningxia Hui Autonomous Region, China: an application of the SWOT-AHP method. Environ Earth Sci 72:1811–1820. doi:10.1007/s12665-014-3090-3

    Article  Google Scholar 

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Acknowledgments

The authors sincerely thank the Tertiary Education Trust Fund and the management of Federal University of Technology, Akure for the award of scholarship to MOGAJI. K. A. The sponsorship assisted the completion of this work and its eventual publication.

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Mogaji, K.A., Omosuyi, G.O., Adelusi, A.O. et al. Application of GIS-Based Evidential Belief Function Model to Regional Groundwater Recharge Potential Zones Mapping in Hardrock Geologic Terrain. Environ. Process. 3, 93–123 (2016). https://doi.org/10.1007/s40710-016-0126-6

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