Potential Detection of the Groundwater Resources Using Analytic Network Process in Geographic Information System(Case Study: Basins Leading to Tabriz Plain)

Document Type : Research Article

Authors

1 Department of Geomorphology, Faculty of Geography and Planning, University of Tabriz

2 M.A. in Remote Sensing and GIS, Faculty of Geography and Planning, University of Tabriz

Abstract

Basins leading to Tabriz plain are part of the sub-basins of Urmia Lake basin, which is located in the east Azerbaijan province and in the north-western part of Iran. The area of this basin is 5397 km2, and Agriculture is one of the main sources of income for the people, which is dependent on groundwater and surface water resources. In this study, an attempt was made to investigate the basins leading to Tabriz plain in terms of potential detection of the groundwater resources using GIS. To achieve this aim, analytic network process and relationships between climate, hydrology, geology, topology, and environmental criteria were applied. Weights of criteria were calculated by analytic network method: geology (0.267), precipitation (0.208), stream density (0.130), vegetation cover (0.119), distance from stream (0.076), fault density (0.054), slope (0.042), distance from fault (0.034), elevation classes (0.028), aspect (0.019), and temperature (0.018). Finally, 5 potential classes including, very high, high, moderate, low, and very low were identified in the study area. The results of the study indicated that regions with high and very high potential often correspond with low elevations and alluvial large grain sediments of fourth era and fans. Also, low and very low potential regions respectively correspond with maximum heights (due to steep slope), and marl and shale regions (due to very low penetranceand high evaporation).
 
 

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Main Subjects

References

 
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Iranian journal of Ecohydrology
Volume 3, Issue 3
September 2017
Pages 379-389

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History

  • Receive Date: 10 November 2016
  • Revise Date: 12 December 2016
  • Accept Date: 19 December 2016
  • First Publish Date: 19 December 2016
  • Publish Date: 22 September 2016

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