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GIS-based bivariate statistical techniques for groundwater potential analysis (an example of Iran)

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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.

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Acknowledgements

The authors would like to thank Iranian Meteorological Organization and Geological Survey of Iran (GSI) for giving meteorological data of Broujerd Station and geology map. Also, authors would like to thank two anonymous reviewers and editorial positive comments.

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Authors and Affiliations

  1. Department of Range and Watershed Management Engineering, Lorestan University, Lorestan, Iran

    Ali Haghizadeh & Davoud Davoudi Moghaddam

  2. Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran

    Hamid Reza Pourghasemi

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  1. Ali Haghizadeh
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  2. Davoud Davoudi Moghaddam
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  3. Hamid Reza Pourghasemi
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Correspondence to Hamid Reza Pourghasemi.

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Corresponding editor: Prashant K Srivastava

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Haghizadeh, A., Moghaddam, D.D. & Pourghasemi, H.R. GIS-based bivariate statistical techniques for groundwater potential analysis (an example of Iran). J Earth Syst Sci 126, 109 (2017). https://doi.org/10.1007/s12040-017-0888-x

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  • DOI: https://doi.org/10.1007/s12040-017-0888-x

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