Morphodynamics and sediment connectivity index in an unmanaged,debris-flow prone catchment:a through time perspective

Torrential processes are among the main actors responsible for sediment production and mobility in mountain catchments.For this reason,the understanding of preferential pathways for sediment routing has become a priority in hazard assessment and mitigation.In this context,the sediment Connectivity Index(IC)enables to analyse the existing linkage between sediment sources and the selected target(channel network or catchment outlet).The IC is a grid-based index that allows fast computation of sediment connectivity based on landscape information derived from a single Digital Terrain Model(DTM).The index computation is based on the log-ratio between an upslope and a downslope component,including information about drainage area,slope,terrain roughness,and distance to the analysis target(e.g.outlet).The output is a map that highlights the degree of structural connectivity of sediment pathways over analysed catchments.Until now,these maps are however rarely used to help defining debris-flow hazard maps,notably due to a lack of guidelines to interpret the IC spatial distribution.This paper proposes an exploitation procedure along profiles to extract more information from the analysis of mapped IC values.The methodology relies on the analysis of the IC and its component variables along the main channel profile,integrated with information about sediment budgeting derived from Difference of DEMs(DoD).The study of connectivity was applied in the unmanaged sub-catchment(without torrent control works)of the Rio Soial(Autonomous Province of Trento–NE Italy)to understanding the geomorphic evolution of the area after five debris flows(in ten years)and the related changes of sediment connectivity.Using a recent DTM as validation,we demonstrated how an IC analysis over the older DTM can help predicting geomorphic changes and associated hazards.The results show an IC aptitude to capture geomorphic trajectories,anticipate debris flow deposits in a specific channel location,and depict preferential routing pathways.

The effect of grid size on the quantification of erosion,deposition,and rill network

Hillslope rill/interrill erosion has been investigated from the perspective of runoff transport of sediment.Recent advances in terrestrial laser scanning can provide high-resolution elevation data up to centimeter levels,and temporal digital elevation models(DEMs)enabled the detection and quantification of sediment redistribution.Erosion and deposition are spatially heterogeneous across hillslopes,and the choice of resolution is critical when using a DEM to study the spatial pattern of the processes.This study investigates the influence of grid size on the sediment change calculation and rill network delineation based on two surveys using a terrestrial laser scanner on a hillslope with well-developed rills in 2014 and 2015.Temporal DEMs were used to quantify elevation changes and used to delineate rill networks.We produced DEM pairs of incremental grid sizes(1-cm,2-cm,5-cm,8-cm,10-cm,15-cm,20-cm,and 30-cm)for DEM difference and rill network delineation.We used the 1-cm DEM as the reference to compare the results produced from other DEMs.Our results suggest that erosion mainly occurs on the rill sidewalls,and deposition on the rill floors,with patches of erosion/deposition within the interrill areas.Both the area and volume of detectable change decrease as the grid size increases,while the area and volume of erosion are less sensitive compared to those of deposition.The total length and number of rills decrease with the increased grid size,whereas the average length of rills increases.The mean offset between delineated rill network and the reference increases with larger grid sizes.In contrast to the erosion and deposition detected within rills,minor changes are detected on the interrill areas,indicating that either no topographic changes occurred or the changes were too small to be detected on the interill areas by our finest 1-cm DEMs.We recommend to use the finest possible grid size that can be achieved for future studies.