Due to increasing climate variability, land-use change, and growing extraction pressures, groundwater recharge and the management of aquifers through managed aquifer recharge (MAR) will play a greater role in the sustainable use of groundwater. However, most studies found that modeling results were highly sensitive to the modeling method, the data used (spatial type), and the dominant controlling processes that determine recharge. This review identified 67 papers published between 2000 and 2025, representing research from 34 countries. Most research is based in areas of high water stress, including Iran (11.9%), the USA (9.0%), India (9.0%), and Australia (7.5%), with the newly added Qatar study further expanding the geographical coverage. In most models, climate remained the primary input (61.2% of studies), followed by monitoring and abstraction data (52.2%), land surface and catchment spatial data (46.3%), and hydrogeological properties of aquifers (37.3%). Key factors included infiltration–runoff partitioning, vadose-zone transmission losses, aquifer heterogeneity, coastal salinity dynamics, and human impacts such as pumping, recharge-site selection, and operational constraints on MAR. Scenario-based modeling was often used to examine the effects of climate change, land use changes, site-selection strategies, and management interventions (50.7%); however, only 28.4% of scenarios included uncertainty quantification, revealing a significant methodological gap. Most scenarios were calibrated (70.1%), but independent validation was performed less frequently (41.8%), resulting in ongoing equifinality and structural uncertainty in recharge estimation. To support future transferability and decision-making in MAR and recharge modeling, standardized reporting of modeling inputs and assumptions, improved vadose-zone and subsurface characterization, and the development of uncertainty-aware evaluation frameworks are necessary.
Khan et al. (Fri,) studied this question.