
NAME:
SOWI - HS 3
BUILDING:
SOWI
FLOOR:
0
TYPE:
Lecture Hall
CAPACITY:
140
ACCESS:
Only Participants
EQUIPMENT:
Beamer, PC, WLAN (Eduroam), Overhead, Blackboard, Sound System, Microphones, Handicapped Accessible
Mountain landscapes are influenced by geomorphological processes such as debris flows. These affect both their infrastructures and ecosystems, and the assessment of their magnitude and frequency is key to land management and risk assessment. On the other hand, the reconstruction of their past activity remains a challenge due to the scarcity of continuous historical records. To fill this gap, a dendrogeomorphological study was conducted on an alluvial cone in the Pineta Valley (Central Pyrenees, Spain). A total of 924 tree samples (851 cores and 73 cross-sections) from 758 disturbed trees were collected, allowing the identification of growth disturbances linked to past events. These data were complemented by detecting geomorphological changes from multitemporal LiDAR analysis over the last three and aerial picture recognitions, which provided additional insights into surface modifications and supported the tree-ring-based reconstructions. Analyses of the unprecedented number of trees analyzed suggest a complex history of debris flow activity, with variations in both magnitude and frequency over time. These results reveal trend changes potentially related to climatic conditions and dissimilar sediment connectivity. Using dendrochronology with LiDAR-based analysis of the terrain, a detailed spatio-temporal reconstruction was carried out, providing insight into the dynamics and triggers of debris flows. This integrated approach contributes to better hazard assessment and to identifying factors and periods of different levels of activity. The use of tree ring records combined with high-resolution topographic data highlights the importance of integrating different methodologies for the reconstruction of past geomorphological processes. These findings provide insight into the dynamics of debris flows in mountain landscapes and highlight the importance of using tree rings in conjunction with remote sensing for risk assessment.

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