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Original Articles

Evaluation of aquifer vulnerability using PCA technique and various clustering methods

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Pages 2117-2140 | Received 19 Aug 2019, Accepted 11 Oct 2019, Published online: 21 Nov 2019

References

  • Abonyi J, Feil B. 2007. Cluster analysis for data mining and system identification. Berlin (Germany): Springer Science & Business.
  • Aller L, Bennet T, Lehr JH, Petty RJ, Hachet G. 1987. DRASTIC: a standardised system for evaluating groundwater pollution potential using hydrogeologic settings (EPA 600/2-00). Environmental Research Laboratory, Office of Research and Development, US Environmental Protection Agency Report, Tucson, 622.
  • Alizadeh MJ, Kavianpour MR, Kisi O, Nourani V. 2017. A new approach for simulating and forecasting the rainfall-runoff process within the next two months. J Hydrol. 548:588–597.
  • Arezoomand OLM, KHashei SA, Javadi S, Hashemi S. 2015. Groundwater Vulnerability Assessment by the use of DRASTIC-NW modified model (Case Study: Kuchesfehan-Astane Plain). Ain Shams Eng J. 7(1):11–20.
  • Asadi P, Ataie-Ashtiani B, Beheshti A. 2017. Vulnerability assessment of urban groundwater resources to nitrate: the case study of Mashhad, Iran. Environ Earth Sci. 76(1):41.
  • Al-Zabet T. 2002. Evaluation of aquifer vulnerability to contamination potential using the DRASTIC method. Environ Geol. 43(1–2):203–208.
  • Babiker IS, Mohamed MA, Hiyama T, Kato K. 2005. A GIS-based DRASTIC model for assessing aquifer vulnerability in Kakamigahara Heights, Gifu Prefecture, central Japan. Sci Total Environ. 345(1–3):127–140. ‏
  • Balazs F. 2006. Fuzzy clustering in process of data mining (PhD thesis). Department of Process Engineering, University of Veszprem Hungry, p. 157.
  • Caliendo C, Parisi A. 2005. Principal component analysis applied to crash data on multilane roads. Proceedings of Third International SIIV Congress. http://www.sed.siiv.scelta.com/bari2005/080.pdf.
  • Chang F-J, Huang C-W, Cheng S-T, Chang L-C. 2017. Conservation of groundwater from over-exploitation—scientific analyses for groundwater resources management. Sci Total Environ. 598:828–838.
  • Choubin B, Solaimani K, Roshan MH, Malekian A. 2017. Watershed classification by remote sensing indices: a fuzzy c-means clustering approach. J Mt Sci. 14(10):2053–2063. ‏
  • Davies DL, Bouldin DW. 1979. A cluster separation measure. IEEE Trans Pattern Anal Mach Intell. 1(2):224–227.
  • Dash, Rajashree, Rasmita Dash, and Debahuti Mishra. “A hybridized rough-PCA approach of attribute reduction for high dimensional data set.” European Journal of Scientific Research 44, no. 1 (2010): 29–38.
  • Denny SC, Allen DM, Journeay JM. 2007. DRASTIC-Fm: a modified vulnerability mapping method for structurally controlled aquifers in the southern Gulf Islands, British Columbia, Canada. Hydrogeol J. 15(3):483. ‏
  • Feil B. 2006. Fuzzy clustering in process of data mining (PhD thesis). Department of Process Engineering, University of Veszprem Hungary.
  • Fernandez-Cano A. 2016. A methodological critique of the PISA evaluations. Relieve 22(1):1–16.
  • Fijani E, Nadiri AA, Moghaddam AA, Tsai FT-C, Dixon B. 2013. Optimization of DRASTIC method by supervised committee machine artificial intelligence to assess groundwater vulnerability for Maragheh–Bonab plain aquifer, Iran. J Hydrol. 503:89–100.
  • Ghosh S, Dubey SK. 2013. Comparative analysis of k-means and fuzzy c-means algorithms. IJACSA. 4(4).
  • Gogu RC, Hallet V, Dassargues A. 2003. Comparison of aquifer vulnerability assessment techniques. Application to the Néblon river basin (Belgium). Environ Geol. 44(8):881–892.
  • Güler C, Kurt MA, Alpaslan M, Akbulut C. 2012. Assessment of the impact of anthropogenic activities on the groundwater hydrology and chemistry in Tarsus coastal plain (Mersin, SE Turkey) using fuzzy clustering, multivariate statistics and GIS techniques. J Hydrol.414–415:435–451.
  • Hao, J., Zhang, Y., Jia, Y., Wang, H., Niu, C., Gan, Y. and Gong, Y., 2017. Assessing groundwater vulnerability and its inconsistency with groundwater quality, based on a modified DRASTIC model: a case study in Chaoyang District of Beijing City. Arabian Journal of Geosciences, 10(6), p.144.
  • Hashemy, SM. and Monem, MJ. 2012. Facilitation of operation and maintenance activities of irrigation networks using ak-means clustering method: case study of the ghazvin irrigation network. Irrigation and drainage, 61(1), pp.31–38.
  • Harter W. 2001. Assessing vulnerability of groundwater. Agriculture and Natural Resources. Publication 3497.
  • Iqbal J, Gorai A, Tirkey P, Pathak G. 2012. Approaches to groundwater vulnerability to pollution: a literature review. Asian J Water Environ Pollut. 9(1):105–115.
  • Javadi S, Kavehkar N, Mousavizadeh MH, Mohammadi K. 2011. Modification of DRASTIC model to map groundwater vulnerability to pollution using nitrate measurements in agricultural areas. J Agric Sci Technol. 13:239–249.
  • Javadi S, Hashemy SM, Mohammadi K, Howard K, Neshat A. 2017. Classification of aquifer vulnerability using K-means cluster analysis. J Hydrol. 549:27–37.
  • Javadi S, Hashemy SM. 2016. Evaluation of groundwater vulnerability using data mining technique in Hashtgerd plain. J Earth Space Phys. 42(4):35–41.
  • Jolliffe I. 2011. Principal component analysis: international encyclopedia of statistical science. Berlin (Germany): Springer. p. 1094–1096.
  • Johnson RA, Wichern DW. 1982. Applied multivariate statistics. Englewood Cliffs (NJ): Prentice Hall.
  • Kim DW, Lee KH, Lee D. 2004. On cluster validity index for estimation of the optimal number of fuzzy clusters. J Pattern Recog Soc. 37:209–225.
  • Kihumba AM, Vanclooster M, Longo JN. 2017. Assessing groundwater vulnerability in the Kinshasa region, DR Congo, using a calibrated DRASTIC model. J Afr Earth Sci. 126:13–22.
  • Khosravi K, Pham BT, Chapi K, Shirzadi A, Shahabi H, Revhaug I, Prakash I, Bui DT. 2018. A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran. Sci Total Environ. 627:744–755.
  • Koh, DC., Kim, EY., Ryu, JS. and Ko, KS. 2009. Factors controlling groundwater chemistry in an agricultural area with complex topographic and land use patterns in mid-western South Korea. Hydrological processes, 23(20):2915–2928.
  • Li C, Sun L, Jia J, Cai Y, Wang X. 2016. Risk assessment of water pollution sources based on an integrated k-means clustering and set pair analysis method in the region of Shiyan, China. Sci Total Environ. 557:307–316.
  • Li F, Zhu J, Deng X, Zhao Y, Li S. 2018. Assessment and uncertainty analysis of groundwater risk. Environ Res. 160:140–151.
  • Lowe M, Hurlow HA, Matyjasik M. 2003. The Weber River basin aquifer storage and recovery project, Utah Geological Survey.
  • Machiwal D, Jha MK, Singh VP, Mohan C. 2018. Assessment and mapping of groundwater vulnerability to pollution: current status and challenges. Earth-Sci Rev. 185:901.
  • Mokhtari HR, Espahbod MR. 2009. The investigation of hydrodynamic parameters potentiality of the Varamin plain regarding the variation of salinity gradient. J Earth. 4(2):27–47.
  • Monem, M. J., & Hashemy, S. M. (2010). Extracting physical homogeneous regions out of irrigation networks using fuzzy clustering method: a case study for the Ghazvin canal irrigation network. Journal of Hydroinformatics, 13(4), 652–660.
  • Nadiri AA, Sedghi Z, Khatibi R, Sadeghfam S. 2018. Mapping specific vulnerability of multiple confined and unconfined aquifers by using artificial intelligence to learn from multiple DRASTIC frameworks. J Environ Manag. 227:415–428.
  • Neshat A, Pradhan B, Pirasteh S, Shafri HZM. 2014. Estimating groundwater vulnerability to pollution using a modified DRASTIC model in the Kerman agricultural area, Iran. Environ Earth Sci. 71(7):3119–3131.
  • Nourzadeh, M., Hashemy, SM., Rodriguez Martin, JA., Bahrami, HA. and Moshashaei, S. 2013. Using fuzzy clustering algorithms to describe the distribution of trace elements in arable calcareous soils in northwest Iran. Archives of Agronomy and Soil Science, 59(3):435–448.
  • Pacheco F, Martins L, Quininha M, Oliveira AS, Fernandes LS. 2018. Modification to the DRASTIC framework to assess groundwater contaminant risk in rural mountainous catchments. J Hydrol. 566:175–191.
  • Patrikaki O, Kazakis N, Voudouris K. 2012. Vulnerability map: a useful tool for groundwater protection: an example from Mouriki basin, north Greece. Fresenius Environ Bull. 21(8c):2516–2521.
  • Razandi Y, Pourghasemi HR, Neisani NS, Rahmati O. 2015. Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS. Earth Sci Inform. 8(4):867–883.
  • Ribeiro L, Pindo JC, Dominguez-Granda L. 2017. Assessment of groundwater vulnerability in the Daule aquif Ecuador, using the susceptibility index method. Science of the Total Environment. 574:1674–1683.
  • Roy DK, Datta B. 2017. Fuzzy C-mean clustering based inference system for saltwater intrusion processes prediction in coastal aquifers. Water Resour Manage. 31(1):355–376.
  • Saldarriaga JF, Gallego JL, López JE, Aguado R, Olazar M. 2019. Selecting monitoring variables in the manual composting of municipal solid waste based on principal component analysis. Waste Biomass Valor.Valorization10(7):1811–1819. ‏
  • See EG, Ketchen DJ, Jr., Shook CL. 1996. The application of cluster analysis in Strategic Management Research: An analysis and critique. Strat Mgmt J. Journal. 17(6):441–458.
  • Sadeghfam S, Hassanzadeh Y, Nadiri AA, Zarghami M. 2016. Localization of groundwater vulnerability assessment using catastrophe theory. Water Resour Manage. 30(13):4585–4601.
  • Sun CZ, Zuo HJ, Luan TX. 2007. Research on groundwater vulnerability assessment of the lower Liaohe River Plain. J Jilin Univ (Earth Sci Ed). 5:943–948.
  • Stigter T, Ribeiro L, Dill AC. 2006. Evaluation of an intrinsic and a specific vulnerability assessment method in comparison with groundwater salinisation and nitrate contamination levels in two agricultural regions in the south of Portugal. Hydrogeol J. 14(1–2):79–99.
  • Singh KP, Malik A, Mohan D, Sinha S. 2004. Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)—a case study. Water Res. 38(18):3980–3992.
  • Shrestha S, Kafle R, Pandey VP. 2017. Evaluation of index-overlay methods for groundwater vulnerability and risk assessment in Kathmandu Valley, Nepal. Sci Total Environ. 575:779–790. ‏
  • Su, Xiaosi, Wenzhen Yuan, Wei Xu, and Shanghai Du. 2015. “A groundwater vulnerability assessment method for organic pollution: a validation case in the Hun River basin, Northeastern China.” Environmental earth sciences 73(1):467–480.
  • Valente de Oliveira J, Pedrycz W. 2007. Advances in fuzzy clustering and its applications. London (UK): John Wiley and Sons.
  • Vias J, Andreo B, Perles M, Carrasco F. 2005. A comparative study of four schemes for groundwater vulnerability mapping in a diffuse flow carbonate aquifer under Mediterranean climatic conditions. Environ Geol. 47(4):586–595.
  • Vrba, J. and Zaporozec, A., 1994. Guidebook on mapping groundwater vulnerability. Heise.
  • Wang XJ, Feng GM, Wang LN. 2015. Groundwater vulnerability assessment in plain area of Hainan Province. South-to-North Water Transf Water Sci Technol. 3:548–552.
  • Xu H, Ma C, Lian J, Xu K, Chaima E. 2018. Urban flooding risk assessment based on an integrated k-means cluster algorithm and improved entropy weight method in the region of Haikou, China. J Hydrol. 563:975–986. ‏
  • Xiaosi, Wenzhen Yuan, Wei Xu, and Shanghai Du. 2015. “A groundwater vulnerability assessment method for organic pollution: a validation case in the Hun River basin, Northeastern China.” Environmental earth sciences 73(1):467–480.
  • Zehtabian, GR., Hamedi, SR, and Amiraslani, F. 2005. The study of northern and southern parts of varamin plain based on the role of elements on production potential and fertility.

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