Assessing the effectiveness of the analytic hierarchy process as a groundwater predicting tool (Case study: Ghorve-Dehgolan plain)

Document Type : Research Paper

Authors

1 lorestan university

2 Assistant Professor of University of Tehran, Faculty of Natural Resources

3 Professor, University of Tehran

Abstract
Determination of groundwater potential in respect to increasing trend of water demand in Iran, is found to be an unavoidable and vital subject. The present research was aimed to assess the efficiency analytical hierarchical process (AHP) to identify potential groundwater zones. Initially, five parameters (viz., lithology, annual rainfall, drainage density, lineament density and land slope) were used in Ghorveh-Dehgalan plain. Influencing groundwater potential were selected. A questionnaire was prepared to collect ten experts attitudes to paired comparison of such parameters. The normalized weights of criteria/parameters were determined based on Saaty’s 9 point scale and its importance in specifying groundwater potential zones using analytical hierarchy process (AHP) and eigenvector method. To prepare lineament distribution maps, ETM+ Landsat images and PCI Geomatica were applied. Finally, the set of criteria were integrated by weighted linear combination method using ArcGIS 9.3 software to generate groundwater potential prediction map. The pumping test results collected and overlaid with groundwater potential prediction map. The validation of the groundwater potential prediction map was conducted based on frequency ratio and results of pumping 20 wells in study area. Results from comparing predicted potential of groundwater and by the groundwater specific capacity (SPC) showed 85% accuracy. It was established in the study that the AHP technique is promising of make accurate and reliable prediction, specifically in no-data aquifers.

Keywords


Volume 70, Issue 4
Winter 2018
Pages 869-879

  • Receive Date 16 November 2013
  • Revise Date 14 February 2018
  • Accept Date 26 July 2015
  • Publish Date 22 December 2017