Ali Akbar Taghipour

Assistant Professor of Geography and Urban Planning


  • Ph.D. 2014

    Geography and Urban Planning

    University of Tabriz, Tabriz, Iran

  • M.Sc. 2009

    Geography and Urban Planning

    University of Tabriz, Tabriz, Iran

  • B.Sc. 2006

    Geography and Urban Planning

    Ferdowsi University of Mashhad, Mashhad, Iran

Selected Publications

Gorgij, A.D., Kisi, O., Moghaddam, A.A., Taghipour, A. Groundwater quality ranking for drinking purposes, using the entropy method and the spatial autocorrelation index (2017) Environmental Earth Sciences, 76 (7), art. no. 269, .

DOI: 10.1007/s12665-017-6589-6

Groundwater quality for drinking purposes has been evaluated for 21 groundwater samples from the Azarshahr Plain in Iran using entropy theory, and its results have been compared with the spatial autocorrelation of effective parameters of water quality. In order to prevent the expert judgments of the parameters weight that occurs when the Water Quality Index (WQI) method is used, the entropy method was used. Entropy and its weight were calculated, and parameters spatial autocorrelation was then determined. The spatial autocorrelation assessment confirmed the entropy theory results. The maximum spatial autocorrelation, minimum entropy and therefore the highest effectiveness rate on groundwater quality of Azarshahr Plain were found to be associated with bicarbonate. Using the entropy weighted WQI, the groundwater quality was classified into five categories: excellent, good, moderate, poor and extremely poor. According to the entropy weighted WQI, the groundwater quality of study area can be classified into “good” to “poor” domains. © 2017, Springer-Verlag Berlin Heidelberg.

AUTHOR KEYWORDS: Azarshahr Plain; Entropy theory; Groundwater quality; Spatial autocorrelation; World Health Organization
INDEX KEYWORDS: Autocorrelation; Groundwater; Potable water, Azarshahr Plain; Effective parameters; Entropy methods; Entropy theory; Expert judgment; Spatial autocorrelations; Water quality indexes; World Health Organization, Water quality, autocorrelation; bicarbonate; drinking water; entropy; index method; numerical method; spatial analysis; water quality; World Health Organization, Iran
PUBLISHER: Springer Verlag