The evaluation of the morphological dynamics of rivers is increasingly focusing, in recent years, on the achievement of quantitative estimates of change in order to identify geomorphic trends and forecast targeted restoration actions. Thanks to the development of more effective and reliable survey technologies, more accurate Digital Elevation Models (DEM) can be produced and, through their consequent differencing (DoD), extremely useful geomorphic analyses can be carried out. In this situation, a major role is played by uncertainty, especially in the final volumetric rates of erosion and deposition processes, that may lead to misinterpretation of spatial and temporal changes. This paper aims at achieving precise geomorphic estimates derived from subsequent hybrid (LiDAR and bathymetric points) surface representations. The study areas consist of gravel-bed reaches of two differently impacted fluvial environments, Piave and Tagliamento rivers, that were affected by two severe flood events (Piave, R.I. of 7 and 10 years and Tagliamento, R.I. of 15 and 12 years) in the inter-surveys period. The basic Hybrid Digital Elevation Models (HDTM) were processed accounting for spatially variable uncertainty and considering, beside slope and point density input variables, a novel component measuring the quality of the bathymetric derived points. In fact, since the major changes occur within river channels, the integration of this variable evaluating the precision of the bathymetric channel elevations in the HDTMs, has allowed, through the creation of targeted FIS (Fuzzy Inference System) rules, to obtain reliable geomorphic estimates of change. Volumes and erosion and deposition patterns were then analyzed and compared to outline the different dynamics among the sub-reaches and the two river systems.
Evaluation of short-term geomorphic changes in differently impacted gravel-bed rivers using improved dems of difference
