Sinkhole Susceptibility Mapping in Data-Scarce Areas at Small Scales

At a national scale, homogeneous data for sinkhole susceptibility mapping are scarce in Germany. The individual German geological surveys collect relevant data in their respective federal states, resulting in heterogeneous datasets. However, certain tasks, such as the search for a final nuclear waste repository, require homogeneous data coverage across the entire country.

To enable such an approach, we homogenised the karst feature inventories from multiple federal states and selected publications. This compilation provides point data on the spatial occurrence of generalised karst features, such as sinkholes and caves. We derived information on the presence of subrosion-prone rocks from both the General Geological Map of the Federal Republic of Germany and the Hydrogeological Map of Germany.

Due to differing subrosion rates, we distinguish between three types: carbonate karst, chloride karst and sulphate karst. We assigned one or more karst type to each feature in the merged karst inventory and generated a separate susceptibility map for each type.

Using average nearest neighbour analysis, we demonstrate that karst features are spatially clustered and derive a buffer distance to delineate areas of high susceptibility around these features. We classified areas underlain by known karst-prone rocks as having medium sinkhole susceptibility. The final sinkhole susceptibility map is generated by combining these two binary layers, thus depicting karst-prone areas in Germany susceptible to sinkhole formation at a scale of 1:250,000.

The results are validated using borehole data from the Borehole Map of Germany, including information on karst-prone horizons and geohazard maps from individual federal states.

Our results demonstrate a pathway for sinkhole susceptibility mapping in data-scarce regions.