Mapping groundwater potential field using catastrophe fuzzy membership functions and Jenks optimization method: a case study of Maragheh-Bonab plain, Iran

Environmental Earth Sciences

Volumn 75, Issue 7, 2016, Pages

  Sadeghfam, Sina ^a   Hassanzadeh, Yousef ^a   Nadiri, Ata Allah ^a   Khatibi, Rahman ^b  

^a UNIVERSITY OF TABRIZ   (Iran)

^b GTEV ReX Limited   (United Kingdom)

Author keywords

Catastrophe theory; Decision making; Groundwater potential; Objectivity; Subjectivity

Indexed keywords

AQUIFERS; DATA INTEGRATION; DECISION MAKING; DECISION THEORY; DISASTERS; GROUNDWATER; GROUNDWATER RESOURCES; HYDROGEOLOGY; ITERATIVE METHODS;

CATASTROPHE FUNCTIONS; CATASTROPHE THEORY; FUZZY MEMBERSHIP FUNCTION; GROUNDWATER POTENTIALS; INTEGRATING INFORMATION; ITERATIVE IDENTIFICATION; OBJECTIVITY; SUBJECTIVITY;

MEMBERSHIP FUNCTIONS;

ANALYTICAL FRAMEWORK; AQUIFER; CATASTROPHE THEORY; DATA ACQUISITION; DECISION MAKING; ESTIMATION METHOD; FUNCTIONAL ROLE; FUZZY MATHEMATICS; GROUNDWATER RESOURCE; HYDRAULIC PROPERTY; IDENTIFICATION METHOD; MAPPING METHOD; ONE-DIMENSIONAL MODELING; OPTIMIZATION; POTENTIAL FLOW; STUDY METHOD;

BONAB; EAST AZERBAIJAN; IRAN; MARAGHEH;

EID: 84961684177     PISSN: 18666280     EISSN: 18666299     Source Type: Journal    
DOI: 10.1007/s12665-015-5107-y     Document Type: Article

References (31)

1. Ahmed K, Shahid S, Bin Harun S, Ismail T, Nawaz N, Shamsudin S (2014) Assessment of groundwater potential zones in an arid region based on catastrophe theory. Earth Sci Inform 8:539–549. doi:10.1007/s12145-014-0173-3
2. Chen Y, Song G, Yang F, Zhang S, Zhang Y, Liu Z (2012) Risk assessment and hierarchical risk management of enterprises in chemical industrial parks based on catastrophe theory. Int J Environ Res Public Health 9:4386–4402. doi:10.3390/ijerph9124386
3. Cheng CH, Liu YH, Lin Y (1996) Evaluating a weapon system using catastrophe series based on fuzzy scales. In: Proceedings of soft computing in intelligent systems and information. IEEE, pp 212-217. doi:10.1109/AFSS.1996.583593
4. Chowdhury A, Jha MK, Chowdhary VM, Mal BC (2009) Integrated remote sensing and GIS-based approach for accessing groundwater potential in west Medinipur district, West Bengal, India. Int J Remote Sens 30:231–250. doi:10.1080/01431160802270131
5. Crippen RE (1990) Calculating the vegetation index faster. Remote Sens Environ 34:71–73. doi:10.1016/0034-4257(90)90085-Z
6. Dhar A, Sahoo S, Sahoo M (2015) Identification of groundwater potential zones considering water quality aspect. Environ Earth Sci 74:5663–5675. doi:10.1007/s12665-015-4580-7
7. 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. Hydogeol J 6:394–404. doi:10.1007/s100400050162
8. Emberger L (1930) La végétation de la région méditérranéenne. Essai d’une classification des groupements végétaux. Revue de Botanique n 503:642–662
9. Jaiswal RK, Mukherjee S, Krishnamurthy J, Saxena R (2003) Role of remote sensing and GIS techniques for generation of groundwater prospect zones towards rural development–an approach. Int J Remote Sens 24:993–1008. doi:10.1080/01431160210144543
10. Jasmin I, Mallikarjuna P (2014) Delineation of groundwater potential zones in Araniar River basin, Tamil Nadu, India: an integrated remote sensing and geographical information system approach. Environ Earth Sci 73:3833–3847. doi:10.1007/s12665-014-3666-y
11. Jenks GF (1967) The data model concept in statistical mapping. Int Yearb Cartogr 7:186–190
12. Jha M, 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. doi:10.1007/s11269-006-9024-4
13. Karanth KR, Seshu Babu K (1978) Identification of major lineaments on satellite imagery and on aerial photographs for delineation for possible potential groundwater zones in Penukonda and Dharmavaram taluks of Anantapur district. In: Proceedings of joint Indo US workshop on remote sensing of water resources. NRSA, Hyderabad, pp 188–197
14. Khatibi R (2014) Introducing “arithmetic calculus” with some applications: new terms, definitions, notations and operators. J Appl Math 5:2909–2934. doi:10.4236/am.2014.519277
15. Machiwal D, Rangi N, Sharma A (2014) Integrated knowledge-and data-driven approaches for groundwater potential zoning using GIS and multi-criteria decision making techniques on hard-rock terrain of Ahar catchment, Rajasthan, India. Environ Earth Sci 73:1871–1892. doi:10.1007/s12665-014-3544-7
16. Madani A, Niyazi B (2015) Groundwater potential mapping using remote sensing techniques and weights of evidence GIS model: a case study from Wadi Yalamlam basin, Makkah Province, Western Saudi Arabia. Environ Earth Sci 74:5129–5142. doi:10.1007/s12665-015-4524-2
17. Nag SK, Ghosh P (2012) Delineation of groundwater potential zone in Chhatna Block, Bankura District, West Bengal, India using remote sensing and GIS techniques. Environ Earth Sci 70:2115–2127. doi:10.1007/s12665-012-1713-0
18. 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. doi:10.1016/j.jhydrol.2014.02.053
19. Ni J, Ding F, Yu H (2015) Catastrophe theory-based water quality evaluation model under uncertain environment, case in Chaohu Lake. In: Proceedings of the ninth international conference on management science and engineering management. Springer, Berlin, Heidelberg, pp 903–916. doi:10.1007/978-3-662-47241-5_76
20. 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. doi:10.1016/j.jhydrol.2011.10.010
21. Pinto D, Shrestha S, Babel MS, Ninsawat S (2015) Delineation of groundwater potential zones in the Comoro watershed, Timor Leste using GIS, remote sensing and analytic hierarchy process (AHP) technique. Appl water Sci 1–17. doi:10.1007/s13201-015-0270-6
22. Prasad RK, Mondal NC, Banerjee P, Nandakumar MV, Singh VS (2008) Deciphering potential groundwater zone in hard rock through the application of GIS. Environ Geol 55:467–475. doi:10.1007/s00254-007-0992-3
23. Preeja KR, Joseph S, Thomas J, Vijith H (2011) Identification of groundwater potential zones of a tropical river basin (Kerala, India) using remote sensing and GIS techniques. J Indian Soc Remote Sens 39:83–94. doi:10.1007/s12524-011-0075-5
24. Sankar K (2002) Evaluation of groundwater potential zones using remote sensing data in upper Vaigai river basin, Tamilnadu, India. J Indian Soc Remote Sens 30:119–129. doi:10.1007/BF02990644
25. Shankar MNR, Mohan G (2006) Assessment of the groundwater potential and quality in Bhatsa and Kalu river basins of Thane district, western Deccan Volcanic Province of India. Environ Geol 49:990–998. doi:10.1007/s00254-005-0137-5
26. Sree Devi PD, Srinivasulu S, Raju KK (2001) Hydrogeomorphological and groundwater prospects of the Pageru river basin by using remote sensing data. Environ Geol 40:1088–1094. doi:10.1007/s002540100295
27. Thilagavathi N, Subramani T, Suresh M, Karunanidhi D (2015) Mapping of groundwater potential zones in Salem Chalk Hills, Tamil Nadu, India, using remote sensing and GIS techniques. Environ Monit Assess 187:1–17. doi:10.1007/s10661-015-4376-y
28. Todd DK, Mays LW (2005) Groundwater hydrology. Wiley, New Jersey
29. Wang W, Liu S, Zhang S, Chen J (2011) Assessment of a model of pollution disaster in near-shore coastal waters based on catastrophe theory. Ecol Model 222:307–312. doi:10.1016/j.ecolmodel.2010.09.007
30. Xiao-jun W, Jian-yun Z, Shahid S, Xing-hui X, Rui-min H, Man-ting S (2014) Catastrophe theory to assess water security and adaptation strategy in the context of environmental change. Mitig Adapt Strategies Glob Chang 19:463–477. doi:10.1007/s11027-012-9443-x
31. Zhang TJ, Ren SX, Li SG, Zhang TC, Xu HJ (2009) Application of the catastrophe progression method in predicting coal and gas outburst. Int J Min Sci Technol 19:430–434. doi:10.1016/S1674-5264(09)60080-6