Spatial Prediction of Groundwater Potential of Upper Tigris Basin Mapping in Türkiye with GIS-Based Multicriteria Decision Making (MCDM) Method

Abstract

The Upper Tigris region in the Middle East is in Turkey and this study shows it to be an area with significant water resources that enable agricultural activities in the region. Since the GAP irrigation project, yet to be completed, there is an extensive use of groundwater for irrigation. This situation threatens the groundwater potential of the basin. Therefore, determination of groundwater potential should be evaluated properly instead of relying assessment of the groundwater potential of the region with observation wells, which is a more costly method. In this study, the groundwater potential of the basin was determined by the GIS-based Multi-Criteria Decision Making (MCDM) method; the GIS-based-AHP method is used for identifying the groundwater potential zones of the Upper Tigris Basin as an alternative to expensive and time-consuming method of well drilling. There are 8 key criteria considered; Geomorphology (GM), Geology(G), Line Density (LD), Slope (SL), Drainage Density (DD), Land Use (LU), Rainfall (R), and Soil Type (ST) and the individual weight of each criterion was evaluated by the AHP technique and utilized by the “Spatial Analysis Overlay Weighted Method” obtaining the “Groundwater Potential Index (GWPI)”. The GWPI values obtained is used to classify the Upper Tigris Basin into five categories as follows: 319 km2 of the basin has very poor potential (3.8%); 2217 km2 has poor potential (26.7%); 2800 km2 has moderate potential (33.7%); 2200 km2 has good potential (26.5%); and finally, 763 km2 has very good potential (9.2%).

Keywords

• Diyarbakır basin
• groundwater potential
• the AHP Multi-Cretia Decision Making (MCDM) Method
• GIS

References

1. Abdalla, F.: Mapping of groundwater prospective zones using remote sensing and GIS techniques: a case study from the Central Eastern Desert, Egypt. Journal of African Earth Sciences, 70, 8-17, DOI: 10.1016/j.jafrearsci.2012.05.003, 2012.
2. Adiat, K. A. N., Nawawi, M. N. M., & Abdullah, K.: Assessing the accuracy of GIS-based elementary multicriteria decision analysis as a spatial prediction tool–a case of predicting potential zones of sustainable groundwater resources. Journal of Hydrology, 440, 75-89, DOI: 10.1016/j.jhydrol.2012.03.028, 2012.
3. Akbaş, B., Akdeniz, N., Aksay, A., Altun, İ., Balcı, V., Bilginer, E., Bilgiç, T., Duru, M., Ercan, T., Gedik, İ., Günay, Y., Güven, İ.H., Hakyemez, H. Y., Konak, N., Papak, İ., Pehlivan, Ş., Sevin, M., Şenel, M., Tarhan, N.,Turhan, N., Türkecan, A., Ulu, Ü., Uğuz, M.F., Yurtsever, A. and etc.,: Türkiye Jeoloji Haritası Maden Tetkik ve Arama Genel Müdürlüğü Yayını Ankara, 2002.
4. Althuwaynee, O. F., Pradhan, B., Park, H. J., & Lee, J. H.: A novel ensemble bivariate statistical evidential belief function with knowledge-based analytical hierarchy process and multivariate statistical logistic regression for landslide susceptibility mapping. Catena, 114, 21-36, DOI: 10.1016/j.catena.2013.10.011, 2014.
5. Çelik, R.: Temporal changes in the groundwater level in the Upper Tigris Basin, Turkey, determined by a GIS technique. Journal of African Earth Sciences, 107, 134-143, DOI: 10.1016/j.jafrearsci.2015.03.004, 2015.
6. Çelik R. 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. 2019; 11(12):2630. https://doi.org/10.3390/w11122630
7. Doke, A. B., Zolekar, R. B., Patel, H., & Das, S. (2021). Geospatial mapping of groundwater potential zones using multi-criteria decision-making AHP approach in a hardrock basaltic terrain in India. Ecological Indicators, 127, 107685.
8. Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The critic method. Computers & Operations Research, 22(7), 763-770.

9. Eulenstein, F., Saparov, A., Lukin, S., Sheudshen, A. K., Mayer, W. H., Dannowski, R., ... & Cremer, N. (2016). Assessing and controlling land use impacts on groundwater quality. Novel methods for monitoring and managing land and water resources in Siberia, 635-665.
10. Feizizadeh, B.,Jankowski, P., & Blaschke, T.: A GIS based spatially-explicit sensitivity and uncertainty analysis approach formula multi-criteria decision analysis. Computers&geosciences, 64, 81-95, DOI: 10.1016/j.cageo.2013.11.009, 2014.
11. Gale, I., Neumann, I., Calow, R., & Moench, D. M. (2002). The effectiveness of Artificial Recharge of groundwater: a review.
12. Global Land Cover Facility(GLCF): http://glcf.umd.edu/data, last access: 25 October 2018.
13. Greene R.,Devillers R., Luther J. E., and Eddy B. G.: GIS-based multiple-criteria decision analysis, Geography Compass, 5/6, 412–432, DOI: 10.1111/j.1749-8198.2011.00431.x, 2011.
14. Haghizadeh, A., Moghaddam, D. D., & Pourghasemi, H. R.: GIS-based bivariate statistical techniques for groundwater potential analysis (an example of Iran). Journal of Earth System Science, 126(8),109, DOI: 10.1007/s12040-017-0888-x, 2017.
15. Herrmann, F.,Baghdadi, N., Blaschek, M., Deidda, R., Duttmann, R., La Jeunesse, I., ... &Wendland, F.: Simulation of future groundwater recharge using a climate model ensemble and SAR-image based soil parameter distributions—A case study in an intensively-used Mediterranean catchment. Science of the Total Environment, 543, 889-905, DOI: 10.1016/j.scitotenv.2015.07.036, 2016.
16. Ho W.,Xu X. and Dey P.K.: Multi-criteria decision making approaches for supplier valuation and selection: a literature review, European Journal of Operational Research, 202/1, 16–24, DOI: 10.1016/j.ejor.2009.05.009, 2010.
17. Iqbal, J., Gorai, A. K., Katpatal, Y. B., & Pathak, G.: Development of GIS-based fuzzy pattern recognition model (modified DRASTIC model) for groundwater vulnerability to pollution assessment. International journal of environmental science and technology, 12(10), 3161-3174, DOI: 10.1007/s13762-014-0693-x, 2015.
18. Isaev, V.A.; Mikhailova, M.V.: "The hydrology, evolution, and hydrological regime of the mouth area of the Shatt al-Arab River". Water Resources. 36 (4): 380–395, DOI: 10.1134/S0097807809040022, 2009.
19. Islamic encyclopedia: https://islamansiklopedisi.org.tr/dicle, last access: 25 January 2019
20. Jan, C. D., Chen, T. H., & Lo, W. C. (2007). Effect of rainfall intensity and distribution on groundwater level fluctuations. Journal of hydrology, 332(3-4), 348-360.
21. Karnatak, H. C., Saran S., Bhatia K. and Roy P. S.: Multicriteria spatial decision analysis in web GIS environment, Geoinformatica, 11, 407–429, DOI: 10.1007/s10707-006-0014-8, 2007.
22. Kresic, N. (2010). Types and classifications of springs. In Groundwater hydrology of springs (pp. 31-85). Butterworth-Heinemann.
23. Krishnamurthy, J., Mani, A., Jayaraman, V., & Manivel, M.: Groundwater resources development in hard rock terrain-an approach using remote sensing and GIS techniques. International journal of applied earth observation and geoinformation, 2(3-4), 204-215, DOI: 10.1016/S0303-2434(00)85015-1, 2000.
24. Lee, S., Kim, Y. S., & Oh, H. J.: Application of a weights-of-evidence method and GIS to regional groundwater productivity potential mapping. Journal of environmental management, 96(1), 91-105, DOI: 10.1016/j.jenvman.2011.09.016, 2012.
25. Magowe, M., & Carr, J. R.: Relationship between lineaments and ground water occurrence in western Botswana. Groundwater, 37(2), 282-286, DOI: 10.1111/j.1745-6584.1999.tb00985.x, 1999.
26. Makropoulos C.K. and Butler D.: Spatial ordered weighted averaging: incorporating spatially variable attitude towards risk in spatial multi-criteria decision-making, Environmental Modelling& Software, 21/1, 69–84, DOI: 10.1016/j.envsoft.2004.10.010, 2006.
27. Malczewski J.: GIS and Multicriteria Decision Analysis, Wiley & Sons, Toronto, 1999
28. Mallick, J., Khan, R. A., Ahmed, M., Alqadhi, S. D., Alsubih, M., Falqi, I., & Hasan, M. A. (2019). Modeling groundwater potential zone in a semi-arid region of Aseer using fuzzy-AHP and geoinformation techniques. Water, 11(12), 2656.
29. Mahammad, S., & Islam, A. (2021). Evaluating the groundwater quality of Damodar Fan Delta (India) using fuzzy-AHP MCDM technique. Applied Water Science, 11(7), 1-17.
30. Mandal, U., Sahoo, S., Munusamy, S. B., Dhar, A., Panda, S. N., Kar, A., & Mishra, P. K.: Delineation of groundwater potential zones of coastal groundwater basin using multi-criteria decision making technique. Water resources management, 30(12), 4293-4310, DOI: 10.1007/s11269-016-1421-8, 2016.
31. https://mpgm.csb.gov.tr/adiyaman---sanliurfa---diyarbakir-planlama-bolgesi-i-82181
32. Mendoza G.A. and H. Martins,: Multi-criteria decision analysis in natural resource management: A critical review of methods and new modelling paradigms, Forest Ecology and Management, 230/1–3, 1–22, DOI: 10.1016/j.foreco.2006.03.023, 2006.
33. MTA, http://yerbilimleri.mta.gov.tr/anasayfa.aspx, last access: 28 September 2018.
34. Nag A, Ghosh S, Biswas S, Sarkar D, Sarkar P.: An image Steganography technique using X-box mapping. In: 2012 International conference on advances in engineering, science and management (ICAESM), pp 709–713. IEEE, 2012.
35. Nobre, R. C. M., Rotunno Filho, O. C., Mansur, W. J., Nobre, M. M. M., & Cosenza, C. A. N.: Groundwater vulnerability and risk mapping using GIS, modeling and a fuzzy logic tool. Journal of Contaminant Hydrology, 94(3-4), 277-292, DOI: 10.1016/j.jconhyd.2007.07.008, 2007.
36. Ö. Emre, Duman, T.Y., Özalp, S., Elmacı, H., Olgun, Ş. ve Şaroğlu, F.: 1/1.250.000 Ölçekli Türkiye Diri Fay Haritası, Maden Tetkik ve Arama Genel Müdürlüğü Özel Yayınlar Serisi-, Ankara, 2013.
37. Özden, D. M., Keskin, S., Dinç, U., Kapur, S., Akça, E., Şenol, S., & Dinç, O.: 1: 1.000. 000 Ölçekli Türkiye Coğrafi Toprak Veri Tabanı, 2001.
38. Pradhan, B.: A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS. Computers&Geosciences, 51, 350-365, DOI: 10.1016/j.cageo.2012.08.023, 2013.
39. Rahman, M. A.,Rusteberg, B., Gogu, R. C., Ferreira, J. L., &Sauter, M.: A new spatial multi-criteria decision support tool for site selection for implementation of managed aquifer recharge. Journal of environmental management, 99, 61-75, DOI: 10.1016/j.jenvman.2012.01.003, 2012.
40. Rahmati O, Samani AN, Mahdavi M, Pourghasemi HR, Zeinivand H.: Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS. Arab J Geosci 8(9):7059–707, DOI: 10.1007/s12517-014-1668-4, 2015.
41. Reid, M. E., & Iverson, R. M. (1992). Gravity‐driven groundwater flow and slope failure potential: 2. Effects of slope morphology, material properties, and hydraulic heterogeneity. Water Resources Research, 28(3), 939-950.
42. Republic of Turkey Prime Ministry, GAP Regional Development Administration: GAP Bölge Kalkinma Plani 2002 (GAP Development Plan), Ankara, 2002.
43. Saaty T. L.: The Analytic Hierarchy Process, McGraw-Hill, New York, 1980.
44. Saaty, T. L.: Hierarchical-Multi objective Systems, Control-Theory and Advanced Technology, 5, 4, 485-489, 1989.
45. Saaty T.L.: Fundamentals of Decision Making and Priority Theory, RWS Pub., Pittsburgh, 2000.
46. Senanayake, I. P.,Dissanayake, D. M. D. O. K., Mayadunna, B. B., & Weerasekera, W. L.: An approach to delineate groundwater recharge potential sites in Ambalantota, Sri Lanka using GIS techniques. Geoscience Frontiers, 7(1), 115-124, DOI: 10.1016/j.gsf.2015.03.002, 2016.
47. 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 Int 30(4):402–421, DOI: 10.1080/10106049.2014.894584, 2015.
48. Triantaphyllou E, Sanchez A.: A Sensitivity Analysis Approach for some Deterministic Multi-Criteria Decision Making Methods. Decision Sciences, 28(1), 151-194, DOI: 10.1111/j.1540-5915.1997.tb01306.x, 1997.
49. Tarboton, D. G., Bras, R. L., & Rodriguez-Iturbe, I.: A physical basis for drainage density. Geomorphology, 5(1/2), 59-76, DOI: 10.1016/0169-555X(92)90058-V, 1992.
50. Tucker, G. E., & Bras, R. L.: Hillslope processes, drainage density, and landscape morphology. Water Resources Research, 34(10), 2751-2764, DOI: 10.1029/98WR01474, 1998.
51. Turkey Agricultural Ministry, https://www.tarim.gov.tr/sgb/Belgeler/SagMenuVeriler/ TRGM .pdf, last access: 10 December 2018.
52. Turkey State Meteorology, https://www.mgm.gov.tr/veridegerlendirme/il-ve-ilceleristatistik.aspx?k=A&m= DIYARBAKIR, last access: 10 October 2018.
53. Verma, N., & Patel, R. K. (2021). Delineation of groundwater potential zones in lower Rihand River Basin, India using geospatial techniques and AHP. The Egyptian Journal of Remote Sensing and Space Science, 24(3), 559-570.
54. Wang, H., Gao, J. E., Zhang, M. J., Li, X. H., Zhang, S. L., & Jia, L. Z. (2015). Effects of rainfall intensity on groundwater recharge based on simulated rainfall experiments and a groundwater flow model. Catena, 127, 80-91.
55. Zaidi, F. K.,Nazzal, Y., Ahmed, I., Naeem, M., &Jafri, M. K.: Identification of potential artificial groundwater recharge zones in Northwestern Saudi Arabia using GIS and Boolean logic. Journal of African Earth Sciences, 111, 156-169, DOI: 10.1016/j.jafrearsci.2015.07.008, 2015.