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      Permanent link:
      https://www.ias.ac.in/article/fulltext/jess/126/08/0109

    • Keywords

       

      Groundwater; statistical index; Dempster–Shafer theory; water resource management; GIS.

    • Abstract

       

      Groundwater potential analysis prepares better comprehension of hydrological settings of different regions. This study shows the potency of two GIS-based data driven bivariate techniques namely statistical index (SI) and Dempster–Shafer theory (DST) to analyze groundwater potential in Broujerd region of Iran. The research was done using 11 groundwater conditioning factors and 496 spring positions. Based on the ground water potential maps (GPMs) of SI and DST methods, 24.22% and 23.74% of the study area is covered by poor zone of groundwater potential, and 43.93% and 36.3% of Broujerd region is covered by good and very good potential zones, respectively. The validation of outcomes displayed that area under the curve (AUC) of SI and DST techniques are 81.23% and 79.41%, respectively, which shows SI method has slightly a better performance than the DST technique. Therefore, SI and DST methods are advantageous to analyze groundwater capacity and scrutinize the complicated relation between groundwater occurrence and groundwater conditioning factors, which permits investigation of both systemic and stochastic uncertainty. Finally, it can be realized that these techniques are very beneficial for groundwater potential analyzing and can be practical for water-resource management experts.

    • Author Affiliations

       

      Ali Haghizadeh1 Davoud Davoudi Moghaddam1 Hamid Reza Pourghasemi2

      1. Department of Range and Watershed Management Engineering, Lorestan University, Lorestan, Iran.
      2. Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran.

    • Dates

       
      Published
      17 December 2017
      Manuscript received
      8 September 2016
      Manuscript revised
      21 May 2017
      Accepted
      25 May 2017

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