Karst aquifers serve as reliable water source for a large portion of the world’s population, agriculture and ecosystems. The groundwater flow in karst aquifers is characterized by a complex interplay of fast and slow flow processes. Automatic recession analysis on large datasets of hydrographs have been of great value to understand hydrological process variability across different catchments, scales and regions. Event-based recession analysis of karst hydrographs has been used to characterize karst aquifers for a long time but, to our best knowledge, automatic recession analysis has yet not been applied for karst spring characterization. In this study, we evaluate the applicability of automatic recession extraction methods for analysing the recession characteristics of a large number of karst spring hydrographs. We use an automatic routine that recognizes changes in the semi-logarithmic slopes of the recession to separate conduit and matrix contributions. That way, we fit the already available karst-specific recession models to calculate the master recession coefficients of the conduit and matrix system. We evaluate the performance of the extraction techniques and the fitted karst-specific recession models by comparing the variability among recession coefficients calculated by different models. The outcome will be used to: (1) provide guidelines for automatic recession analysis of karst systems using adapted extraction methods and karst-specific recession models; and (2) infer the comparative importance of conduit and matrix drainage in different catchments.