Identifying Optimal Locations for Artificial Groundwater Recharge by Rainfall in the Kingdom of Bahrain

Abstract

The Kingdom of Bahrain has extremely poor endowment of water resources. In the last four decades, the kingdom has experienced fast-paced socio-economic development and rapid population growth which has been associated with dramatic increase in water demands. To meet these water requirements, heavy reliance on groundwater was made, leading to its over-exploitation and resulting in a significant decline in groundwater levels and serious degradation in its quality due to saltwater intrusion. To rehabilitate groundwater, authorities need to pursue two management approaches: (1) lowering groundwater abstraction to its safe yield through implementing demand management and conservation policies; and (2) augmenting groundwater storage by managed aquifer recharge (MAR). In the latter case, recharge can be made during rainfall extreme events, where relatively large amounts of water become available in a relatively short time and accumulates at surface depressions. These waters can be stored in groundwater by enhancing their infiltration through gravity injection wells. In this research, the optimal locations for MAR in Bahrain are identified by employing a multi-criteria decision-making (MCDM) methodology using geographic information system (GIS). The weighted overlay method (WOA) was implemented to identify optimal MAR locations using eight parameters: geology, geomorphology, soil type, land use/land cover, slope, curvature, drainage density, and distance from lineaments. The highest scores (ranked excellent to very good), indicating the most suitable locations for both rainwater harvesting and MAR, were identified at a number of locations. Then, these locations were validated by actual MAR field projects conducted in Bahrain by the water authorities and the majority of these locations were found in agreement. As next steps, it is recommended to conduct an in-depth investigation at the identified locations using a higher-resolution satellite images with utilities infrastructure maps, and include the depth to groundwater as a criteria for the optimum selection of the sites, to be followed by MAR pilot field investigation, monitoring, and modeling for the highest potential locations.