Managed aquifer recharge (MAR) is a powerful approach to counteracting the negative impacts of overexploited groundwater resources and enhancing groundwater availability in water-scarce regions. One common MAR strategy is aquifer storage and recovery (ASR). Theoretically, the ASR techniques can be adopted for karst systems to store and recover water within the system or to increase the subsurface inflow into the alluvial system from the adjacent upland karst system. However, karst systems present a particular challenge for the application and technical implementation of ASR, due to the associated strong anisotropy and heterogeneity, high runoff dynamics, as well as the underlying uncertainties regarding the available data. This research is oriented to provide a regional scale model of a karst-alluvial system in Lebanon, analyzing the impact of MAR scenarios as well as quantifying boundary inflow to adjacent alluvial systems. For this reason, several model conceptualizations (considering multi-model concepts) and ASR application scenarios are adopted and tested. For transferability, real-world case studies and idealized yet generalizable systems are considered and assessed. The model pre- and postprocessing is entirely script-based and uses open-source tools to ensure sustainable use. An anisotropic fast-marching algorithm is used to create spatially distributed karst channel networks through the Python package pyKasso. In addition, a discrete continuum model is developed (e.g., CfPy), where the stochastic conduit networks are implemented as a large ensemble of the plausible and representative karstic system. The regional karst alluvial model results are also used to make general recommendations for MAR site selection in the karstic study site.