Characterisation of drainage dynamics of karst landscapes over Europe

Karst aquifers play a crucial role as water sources globally, with several European countries relying significantly on them for their water supply. Managing these aquifers is challenging due to their subsurface hydraulic heterogeneity. Hydrological modeling has proven valuable, offering insights into the hydraulic dynamics and management of karst water resources. However, characterizing karst drainage attributes at large catchment and regional scales remains challenging, hindering the incorporation of spatial heterogeneity and complexity in large-scale models and leading to unrealistic estimations in karst regions. This study addresses the issue by providing the first regional estimation of karst drainage attribute across Europe, this attribute is herein called Karstification Index (KI). Leveraging a newly developed automated karst spring recession analysis tool, and extensive climatic and physiographic datasets, we applied a regression-based regionalization model to estimate slow and quick flow parameters in karstic landscapes. By estimating KI as the ratio of quick to slow flow parameters, we were able to identify sub-regions with higher and lower degrees of karstification. Our findings highlight the significance of drainage density metrics, particularly in combination with specific climate signals, as predictors of KI. The regionalization model demonstrated high performance, validated by high R² values, especially in well-gauged European catchments. Encouraged by these results, the analysis is being extended to a global scale, marking the first attempt to estimate karstic drainage attributes globally. We believe that this large-scale parameterization of karstification will enhance regional and global karst water resource management. By improving the parameterization and consideration of karst processes in large-scale hydrological models, our research contributes to a more accurate understanding of karst aquifers on a global scale.