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Testing the predictive capability of the Index of Connectivity (IC) on a 2022 debris-flow event considering the spatial variability of the forcing

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Himmelstoss, Toni ; Rom, Jakob ; Kara, Diana-Eileen ; Betz-Nutz, Sarah ; Altmann, Moritz ; Haas, Florian ; Becht, Michael ; Heckmann, Tobias:
Testing the predictive capability of the Index of Connectivity (IC) on a 2022 debris-flow event considering the spatial variability of the forcing.
2024
Veranstaltung: EGU General Assembly 2024, 14.-19.04.2024, Vienna, Austria.
(Veranstaltungsbeitrag: Kongress/Konferenz/Symposium/Tagung, Moderation/Leitung)

Volltext

Volltext Link zum Volltext (externe URL):
https://doi.org/10.5194/egusphere-egu24-7410

Kurzfassung/Abstract

Sediment connectivity is an important property of geomorphic systems reflecting the potential to route material through themselves and hence modulating the propagation of geomorphic changes. While the relevance of the concept is clear, connectivity cannot be measured directly and the discussion on the best methods to quantify connectivity is still ongoing. Probably the most frequently used approach is based on the index of connectivity (IC) as it was developed by Borselli et al. (2008) and later adapted by Cavalli et al. (2013) for alpine catchments. This index aims at quantifying the structural connectivity that is governed by the spatial configuration and properties of system components. Nevertheless, the predictive capabilities of this index for functional connectivity, i.e. the actual transfer of sediment between the system components, have not been conclusively validated with field data. Most importantly, previous studies have, to our knowledge, not taken into account the spatial variability of the hydrometeorological forcing that leads to different functional connectivity in locations with similar structural connectivity.
In this study, we use a unique dataset to test the predictive capability of the IC for hillslope-channel coupling of debris flows in the Horlachtal, Austria (described by Rom et al., 2023). The dataset consists of aerial imagery and two airborne LiDAR digital elevation models from which n=156 debris flows were mapped and quantified that were triggered by intense rainstorms on July 20th and 23rd, 2022. For this event, adjusted radar data (INCA data from the Austrian meteorological survey, ZAMG, and measurements from weather stations within the study area) give a high-resolution account of the spatial distribution of rainfall intensities and sums. Using these data, each debris flow was characterised with respect to (i) the meteorological forcing that affected its contributing area, (ii) morphometric properties of the latter, (iii) its sediment volume, and (iv) its runout length indicating functional connectivity, i.e. the degree of coupling to the main channel. Then we assessed the influence of structural connectivity (indicated by the IC) and hydrometeorological forcing on the observed functional connectivity. To our knowledge, this is the first study investigating the predictive capacity of the IC taking into account the spatial variability of the forcing. Among others, our results show that the IC is significantly higher for those debris flows that reached the main channel, compared to those that did not.

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Publikationsform:Veranstaltungsbeitrag (unveröffentlicht): Kongress/Konferenz/Symposium/Tagung, Moderation/Leitung
Sprache des Eintrags:Englisch
Institutionen der Universität:Mathematisch-Geographische Fakultät > Geographie > Lehrstuhl für Physische Geographie
DOI / URN / ID:10.5194/egusphere-egu24-7410
Titel an der KU entstanden:Ja
KU.edoc-ID:33492
Eingestellt am: 02. Jul 2024 12:37
Letzte Änderung: 03. Jul 2024 16:12
URL zu dieser Anzeige: https://edoc.ku.de/id/eprint/33492/
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