Using particle swarm optimization algorithm and geospatial information system for potential evaluating of groundwater (case study: Mehran, Iran)

• Published in: Arabian journal of geosciences 2021-06, Vol.14 (12), Article 1139
• Main Authors: Vafaeinejad, Alireza, Mahmoudi Jam, Sasan
• Format: Article
• Language: English
• Subjects: Algorithms; Chlorine; Drainage density; Earth and Environmental Science; Earth science; Earth Sciences; Elevation; Flow mapping; Geographic information systems; Geographical information systems; Groundwater; Groundwater flow; Groundwater potential; Information systems; Land use; Lithology; Optimization; Original Paper; Particle swarm optimization; Resources; Site selection; Soil water; Specific yield; Water resources
• ISSN: 1866-7511; 1866-7538
• DOI: 10.1007/s12517-021-07475-8

One critical issue in the proper management of groundwater resources is identifying the potential of these resources to plan and adopt the proper decisions about their utilization. The current research aims to investigate the potential of groundwater resources using an approach integrated with the particle swarm optimization (PSO) algorithm and geospatial information system (GIS) in Mehran Plain, Iran. Although the PSO algorithm has been applied in some cases to address site selection issues, its application has not yet been addressed in the potential evaluation of groundwater resources. The innovation of this research is the use of PSO algorithm to solve potential evaluation of groundwater resources issue. For this purpose, 13 factors affecting water penetration into the soil and underground water formation were used. The factors include slope, elevation, drainage density, lineament density, T map, K map, recharge map, land use map, lithology map, Synology map, groundwater depth map, well density map, and chlorine map. Then, using the PSO algorithm, each of the maps was first weighed and then combined with a weighted overlay approach in the GIS environment. Finally, two final groundwater potential maps were obtained. The optimization equation was once set equal to the well density map (PSO_well-d), and another time was set equal to the specific yield map (PSO_Sy). To validate the results, the groundwater flow intensity-direction map in the area was used, and it was determined that the PSO_Sy map showed much closer results than those of the PSO_well-d map.