Identification of Possible Groundwater Recharge Areas by Multi-criteria Analysis based on GIS (Case: Dezful – Andimeshk Plain)

The over-drilling of deep wells and the excessive exploitation of groundwater sources cause the groundwater level to decrease daily, resulting in more energy to power pumps. Artificial recharging is the injection of water into a permeable formation to recharge the groundwater aquifer and reuse it with a different regime and quality and by creating additional facilities or changes in the region's natural conditions (Fazl Avali, 1998). Placing artificial recharge systems are one of the basic principles of creating these systems. The selection of sites based on scientific and natural points plays a critical role in the success and efficiency of the development of these systems to achieve the relevant goals. This process must be undertaken with considerable care. Identifying artificial recharge areas and substrates can be accomplished using various methods and parameters. No matter the method used, the results from different studies must be analyzed jointly, and then the most appropriate area for the study must be determined. Due to the presence of various characteristics in location, continuous changes of influential factors, and the need to examine the evaluated criteria, the use of GIS due to special features and capabilities, can be beneficial to this endeavor. The multi-criteria analysis method has been mentioned as a valuable model for integrating information layers in artificial recharge. Numerous studies have been conducted to locate recharging sites for artificial recharge.
Ramalingam and Santhakumar (2002), using GIS and remote sensing techniques, investigated suitable artificial feeding areas in a state in India which considered geomorphological, geological, soil, slope, land use, runoff intensity, and groundwater depth. As part of the research conducted by Hekmatpour et al. (2007), areas of the Varamin plain that can be artificial recharge were identified through classification and layer combining in a GIS environment and using a decision support system to make decisions.