DATASET - Adaptation and implementation of the HOTSED framework for assessing seasonal scenarios and short-term weather extremes in a high-altitude watershed of the Eastern Alps
In this study, we presented the first adaptation and implementation of the HOTSED framework in a high-altitude watershed of the Eastern Italian Alps chosen as pilot area. HOTSED was applied to assess the spatio-temporal variability of sediment source hotspots driven by rainfall-induced surface runoff across different climatic conditions and rainfall intensities. We analyzed four seasonal scenarios and four daily scenarios, including an ordinary event and three extreme events with different return periods (10-year, 30-year, and 50-year). A pre-existing polygon-based geomorphological map was used to spatially define sediment sources across the study area. The geomorphic Potential of each Sediment Source (PSS) was estimated through a qualitative scoring of map attributes, supported by semi-quantitative, spatially distributed indices, including slope, permafrost distribution, and a proxy for frost-cracking incidence on the bedrock. Structural Sediment Connectivity (STC) was estimated using a geomorphometric index based on a Digital Terrain Model. For each scenario, a proxy for the Potential for Sediment Transport (PST) was computed using a rainfall-calibrated index, applying a 0°C ground surface temperature threshold to exclude snow-covered areas. All components were then integrated through a raster-based equation, yielding the HOTSED model. In this dataset, for each analysed scenario, we provide the main raster input data used (i.e., PSS, STC, PST, and the snowfall coefficient δ), as well as the final model outputs. The dataset contains 16 folders: 8 scenarios (i.e., 4 seasonal scenarios + 4 short-term daily scenarios) with 2 different configurations (i.e., catchment outlet and main channels). Each folder contains 5 raster files in GEOTIFF format. A brief description of each raster file is provided in the Supplemental Information of this datasets metadata.
Leibniz Centre for Agricultural Landscape Research
Role: publisher
Position: Computation and Data Service Platform - Workgroup Research Data Management
Phone: +49 33432 82 300
Email: dataservice@zalf.de
Deliverypoint: Eberswalder Strasse 84
City: Müncheberg
Administrativearea: Brandenburg
Postalcode: 15374
Country: Germany
Url:
Manuel La Licata
Role: author
Email: manuel.lalicata@zalf.de
Url:
Ananya Pandey
Role: author
Email: ananya.pandey01@universitadipavia.it
Url:
Michael Maerker
Role: author
Email: michael.maerker@zalf.de
Url:
Marco Cavalli
Role: author
Email: manuel.lalicata@zalf.de
Url:
Roberto Seppi
Role: author
Email: roberto.seppi@unipv.it
Url:
Sara Savi
Role: author
Email: sara.savi@unipv.it
Url:
Michael Märker
Role: projectLeader
Email: michael.maerker@zalf.de
Url:
National Research Council of Italy – Research Institute for Geo-hydrological Protection;Leibniz Centre for Agricultural Landscape Research;University of Pavia
Role: contributor
Created: 2026-01-05
Updated: 2026-01-19
Temporal extent:
date
- CSV
Rights: Restrictions applied to assure the protection of privacy or intellectual property, and any special restrictions or limitations or warnings on using the resource or metadata. Reports, articles, papers, scientific and non - scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: "Data reused from the BonaRes Data Centre www.bonares.de. This data were created as part of the ZALF Datenerfassung's research activities." Although every care has been taken in preparing and testing the data, the ZALF Datenerfassung and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the ZALF Datenerfassung and the BonaRes Data Centre accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The ZALF Datenerfassung and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data.
Language: eng