Identifying barriers for nature-based solutions in flood risk management: An interdisciplinary overview using expert community approach.

The major event that hit Europe in summer 2021 reminds society that floods are recurrent and among the costliest and deadliest natural hazards. The long-term flood risk management (FRM) efforts preferring sole technical measures to prevent and mitigate floods have shown to be not sufficiently effective and sensitive to the environment. Nature-Based Solutions (NBS) mark a recent paradigm shift of FRM towards solutions that use nature-derived features, processes and management options to improve water retention and mitigate floods. Yet, the empirical evidence on the effects of NBS across various settings remains fragmented and their implementation faces a series of institutional barriers. In this paper, we adopt a community expert perspective drawing upon LAND4FLOOD Natural flood retention on private land network (https://www.land4flood.eu) in order to identify a set of barriers and their cascading and compound interactions relevant to individual NBS. The experts identified a comprehensive set of 17 barriers affecting the implementation of 12 groups of NBS in both urban and rural settings in five European regional environmental domains (i.e., Boreal, Atlantic, Continental, Alpine-Carpathian, and Mediterranean). Based on the results, we define avenues for further research, connecting hydrology and soil science, on the one hand, and land use planning, social geography and economics, on the other. Our suggestions ultimately call for a transdisciplinary turn in the research of NBS in FRM.

The Application of Hough Transform and Canny Edge Detector Methods for the Visual Detection of Cumuliform Clouds.

The increase in flying time of unmanned aerial vehicles (UAV) is a relevant and difficult task for UAV designers. It is especially important in such tasks as monitoring, mapping, or signal retranslation. While the majority of research is concentrated on increasing the battery capacity, it is also important to utilize natural renewable energy sources, such as solar energy, thermals, etc. This article proposed a method for the automatic recognition of cumuliform clouds. Practical application of this method allows diverting of an unmanned aerial vehicle towards the identified cumuliform cloud and improving its probability of flying into a thermal flow, thus increasing the flight time of the UAV, as is performed by glider and paraglider pilots. The proposed method is based on the application of Hough transform and Canny edge detector methods, which have not been used for such a task before. For testing the proposed method a dataset of different clouds was generated and marked by experts. The achieved average accuracy of 87% on the unbalanced dataset demonstrates the practical applicability of the proposed method for detecting thermals related to cumuliform clouds. The article also provides the concept of VilniusTech developed UAV, implementing the proposed method.