Mountain basins are characterized by relatively fast land surface dynamics, mainly controlled by erosion and sediment transport processes, which commonly cause geo-hydrological risk. Risk reduction requires sustainable management practices; these rely, among others, on a high-resolution monitoring of the river and watershed sediment dynamics. In this context, the TORRENT project aims to prioritize maintenance interventions and improve watershed management techniques by establishing standardised international methods for monitoring the state and functionality of torrent and river control projects, with case studies across the Friuli Venezia-Giulia region (North-Eastern Italy) and Slovenia. Under the TORRENT project, multi-temporal High-Resolution Topography data (HRT) and GIS (Geographic Information System) environments are employed to analyze sediment dynamics across mountain basins. One of the products of the carried out HRT monitoring campaign is the Difference of DEM (Digital Elevation Model), known as DoD, which provides estimates of the changes in elevation due to erosion and deposition processes. In this study we present two applications that make use of the DoD product to (i) validate a modelling procedure of thickness soil slips estimates and (ii) calibrate a modelling framework for critical soil moisture thresholds of hydrological controlled soil slips. The study area involves the basin of But stream, which is a tributary of the main Tagliamento River. The former modelling procedure is based on a thickness inversion technique of a mass balance equation that exploits measure of ground movements detected from Synthetic Aperture Radar Interferometry (InSAR) data derived from Sentinel-1. Spatial distributions of modelled erosion thickness are compared against the DoD and assessed in terms of Root Mean Square Error (RMSE) and Structural Similarity Index Measure (SSIM). The latter application uses the estimates of DoD surface changes to identify the most suitable soil cohesion values that optimize the model framework performance in terms of potential rainfall-induced failing area.
Application of High-Resolution Topography (HRT) data to enhance modelling for mountain watershed management
Elisa Arnone;Sara Cucchiaro;Eleonora Maset;Juby Thomas;Giorgia Chiarel;Federico Cazorzi
2026-01-01
Abstract
Mountain basins are characterized by relatively fast land surface dynamics, mainly controlled by erosion and sediment transport processes, which commonly cause geo-hydrological risk. Risk reduction requires sustainable management practices; these rely, among others, on a high-resolution monitoring of the river and watershed sediment dynamics. In this context, the TORRENT project aims to prioritize maintenance interventions and improve watershed management techniques by establishing standardised international methods for monitoring the state and functionality of torrent and river control projects, with case studies across the Friuli Venezia-Giulia region (North-Eastern Italy) and Slovenia. Under the TORRENT project, multi-temporal High-Resolution Topography data (HRT) and GIS (Geographic Information System) environments are employed to analyze sediment dynamics across mountain basins. One of the products of the carried out HRT monitoring campaign is the Difference of DEM (Digital Elevation Model), known as DoD, which provides estimates of the changes in elevation due to erosion and deposition processes. In this study we present two applications that make use of the DoD product to (i) validate a modelling procedure of thickness soil slips estimates and (ii) calibrate a modelling framework for critical soil moisture thresholds of hydrological controlled soil slips. The study area involves the basin of But stream, which is a tributary of the main Tagliamento River. The former modelling procedure is based on a thickness inversion technique of a mass balance equation that exploits measure of ground movements detected from Synthetic Aperture Radar Interferometry (InSAR) data derived from Sentinel-1. Spatial distributions of modelled erosion thickness are compared against the DoD and assessed in terms of Root Mean Square Error (RMSE) and Structural Similarity Index Measure (SSIM). The latter application uses the estimates of DoD surface changes to identify the most suitable soil cohesion values that optimize the model framework performance in terms of potential rainfall-induced failing area.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
