Determining Vulnerable Areas of Ajabshir Plain Aquifer Using Drastic Method Optimization by Genetic Algorithm and Fuzzy Logic

Document Type : Research Article

Authors

Department of Earth Sciences, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran

Abstract

In recent decades, increasing of population and development of technology and, consequently, intense agricultural and industrial activities have exposed groundwater resources to a variety of pollutants. Ajabshir plain, located in the southwest of East Azarbaijan province and southeast of Urmia Lake, is one of the areas that has faced groundwater contamination and needs more qualitative studies. In this study, first, the conventional drastic method was used to investigate the potential of nitrate contamination in Ajabshir plain, and then the optimization process was performed using the methods of genetic algorithm and fuzzy logic (Sugeno). The index values in the conventional drastic method were obtained from 87 to 145, as well as the drastic index values obtained by considering the weights of the genetic algorithm and optimization with fuzzy logic, from 47 to 74 and 0.01 to 0.6, respectively. According to the allergy classification the ordinary drastic is located in low, low to medium, and medium to high ranges, in which areas from the north of the plain and the north of Ajabshir city had moderate to high vulnerability index. Also, the optimized variables with genetic algorithm and fuzzy logic are in the safe zone in terms of contamination potential due to lower index values than 79. The normal drastic correlation coefficient, genetic algorithm, and fuzzy logic method with nitrate concentration were 0.2,73, 0.57, and 0.796, respectively. Therefore, the results show the superiority of the fuzzy logic method over other methods.

Keywords

References

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Iranian journal of Ecohydrology
Volume 8, Issue 2
July 2021
Pages 381-395

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History

  • Receive Date: 23 November 2020
  • Revise Date: 12 May 2021
  • Accept Date: 12 May 2021
  • First Publish Date: 16 June 2021
  • Publish Date: 22 June 2021

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