Non perennial Mediterranean Rivers in Europe: Status, pressurs, and challanges for research and management

Non-perennial rivers and streams (NPRS) cover >50% of the global river network. They are particularly predominant in Mediterranean Europe as a result of dry climate conditions, climate change and land use development. Historically, both scientists and policy makers underestimated the importance of NRPS for nature and humans alike, mainly because they have been considered as systems of low ecological and economic value. During the past decades, diminishing water resources have increased the spatial and temporal extent of artificial NPRS as well as their exposure to multiple stressors, which threatening their ecological integrity, biodiversity and ecosystem services. In this paper, we provide a comprehensive overview of the structural and functional characteristics of NPRS in the European Mediterranean, and discuss gaps and problems in their management, concerning their typology, ecological assessment, legislative and policy protection, and incorporation in River Basin Management Plans. Because NPRS comprise highly unstable ecosystems, with strong and often unpredictable temporal and spatial variability - at least as far as it is possible to assess - we outline the future research needs required to better understand, manage and conserve them as highly valuable and sensitive ecosystems. Efficient collaborative activities among multidisciplinary research groups aiming to create innovative knowledge, water managers and policy makers are urgently needed in order to establish an appropriate methodological and legislative background. The incorporation of NPRS in EU-Med River Basin Management Plans in combination with the application of ecological flows is a first step towards enhancing NPRS management and conservation in order to effectively safeguard these highly valuable albeit threatened ecosystems

Digital 3D reconstruction as a research environment in art and architecture history: uncertainty classification and visualisation

The dissertation addresses the still not solved challenges concerned with the source-based digital 3D reconstruction, visualisation and documentation in the domain of archaeology, art and architecture history. The emerging BIM methodology and the exchange data format IFC are changing the way of collaboration, visualisation and documentation in the planning, construction and facility management process. The introduction and development of the Semantic Web (Web 3.0), spreading the idea of structured, formalised and linked data, offers semantically enriched human- and machine-readable data. In contrast to civil engineering and cultural heritage, academic object-oriented disciplines, like archaeology, art and architecture history, are acting as outside spectators. Since the 1990s, it has been argued that a 3D model is not likely to be considered a scientific reconstruction unless it is grounded on accurate documentation and visualisation. However, these standards are still missing and the validation of the outcomes is not fulfilled. Meanwhile, the digital research data remain ephemeral and continue to fill the growing digital cemeteries. This study focuses, therefore, on the evaluation of the source-based digital 3D reconstructions and, especially, on uncertainty assessment in the case of hypothetical reconstructions of destroyed or never built artefacts according to scientific principles, making the models shareable and reusable by a potentially wide audience. The work initially focuses on terminology and on the definition of a workflow especially related to the classification and visualisation of uncertainty. The workflow is then applied to specific cases of 3D models uploaded to the DFG repository of the AI Mainz. In this way, the available methods of documenting, visualising and communicating uncertainty are analysed. In the end, this process will lead to a validation or a correction of the workflow and the initial assumptions, but also (dealing with different hypotheses) to a better definition of the levels of uncertainty.