Potential Evaluation of Underground Water Resource with the Hybrid Approach to Particle Swarm Optimization Algorithm and Geospatial Information Systems (Case Study: Mehran, Ilam)

Document Type : Research Article


1 Masters student of Water and hydraulic structures engineering, Faculty of Civil, Water and Environment Engineering, Shahid Beheshti University, Tehran, Iran

2 Assistant professor, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran

3 Assistant professor of Passive Defense College and Research Institute, Imam Hossein University, Tehran, Iran


One of very important problems in correct managing of groundwater resources is finding potential of this resources to correct planning and deciding for use of them. The purpose of this research is potential evaluation of groundwater resources with the hybrid approach to particle swarm optimization algorithm and geographic information systems in Mehran plain. In this regard and due to evaluation of groundwater resources potential in this area, 13 various factors which have a great impact on level of water permeability in ground and groundwater resources formation Including the slope, height, drainage density, fault density, T map, K map, recharge map, landuse map, lithology map, Sy map, depth of groundwater map, well density map and Cl map, were prepared and classified. Then, by PSO algorithm, each map was assigned weight and with overlay method in GIS combined with each other and at the end 2 final groundwater potential map were obtained, once when that optimization equation equal to the well density map (PSO_chah), and once again when that optimization equation equal to the Sy map (PSO_Sy). In this context, PSO_chah map, 2.56% and PSO_Sy map, 2.40% of area determined as areas with very high potential in case of groundwater resources.


Main Subjects

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Volume 4, Issue 4
January 2018
Pages 1199-1213
  • Receive Date: 31 May 2017
  • Revise Date: 03 July 2017
  • Accept Date: 27 July 2017
  • First Publish Date: 22 December 2017
  • Publish Date: 22 December 2017