Delineation of groundwater recharge potential zones using weighted linear combination method (case study: Kuhdasht plain, Iran)

Extracting groundwater resources in Kuhdasht plain in west of Lorestan province as a suitable and available resources of water for agricultural usage, has been led to decline in groundwater level and reservoir storage, changes in water quality, land subsidence and etc. Artificial recharge plans are one of the alternatives to deal with aforementioned challenges. Present study has been reached with the aim of locating prone areas for artificial recharge plans in Kuhdasht plain. Accordingly, seven layers including lithology, slope, elevation, fault density, stream density, land use, and alluvial thickness were weighted using a weighted linear combination (WLC) method. Finally, extracted map of overlapping these layers using WLC method was classified to five potential classes including 'very high' (۳۱.۴۵% of the area), 'high' (۳۸.۹۴%), 'moderate' (۱۸.۴۳%), 'low' (۶.۰۸%) and 'very low' (۵.۱%).

Keywords:

Groundwater , artificial recharge , Artificial Neural Network , Kuhdasht Plain