GIS-based methods are often used to assess the spatial distribution of mean annual recharge rates of karstic aquifers, but they typically do not provide temporal information about the dynamics of recharge. Numerical models are able to assess the temporal dynamics of recharge but they often provide only a single time series of recharge without any information on spatial distributions of recharge. In this study, we compare a process-based numerical karst model—in which the spatial variability of karst properties is considered statistically using analytical distribution functions—with an independently applied GIS-based recharge estimation method. We find that both methods produce similar spatial distributions of recharge rates. We further demonstrate that similarity between the two methods can only be achieved if the numerical model is calibrated with discharge and hydrochemical data. Using this similarity, we explore the value of the relations between the spatial input information of the GIS-based method and the analytical distributions of the process-based karst model for combined application of the two methods at sites without calibration data.