The forecast of riverbed profile changes is very important for analysing the dynamic evolution of slopes, because it represents the result of the main geomorphological processes. The aim of this paper is to expose a method for predicting sediment transport with a semi-quantitative approach, representing how streambed evolves over time. The predictive model has been implemented through Hec-Ras software, combining an empirical equation [1] both for flow and sediment transport, in order to have a framework to approach the problem of streambed evolution, based on the knowledge of: of climatic features, sediment inflow and river flow rate. Streambank geometric characteristics (i.e., bank heights, slopes, and grain size distribution) have been considered during the modeling procedure. Therefore, the method has been applied to a case study, the Anza River in Piemonte (Northern Italy), to test the model. The Anza River includes a reservoir where can be evaluated the accumulation of sediment. The changes of the riverbed profile calculated showed a massive deposition of gravels and sands, bringing about an upward displacement of the apex of the sedimentation area. A similar behavior was also observed in other catchment basins in mountain areas (e.g. in the basin of the Tartano River in Valtellina, Lombardy). Moreover, the results are comparable with the data on the sediments accumulated in the reservoir, demonstrating that the method might be useful in dealing with the problem and that it is potentially widely applicable. Nevertheless, it still needs to be independently tested in different regions. At this aim, the preliminary knowledge, for each section of the river, about the solid materials inflow and the river discharge are useful for a correct calculation of the riverbed profile change.

GEOMORPHOLOGICAL EVOLUTION OF RIVERBED OF THE ANZA RIVER (PIEDMONT, ITALY): A THEORETICAL FRAMEWORK

COLOMBO, LORIS;FRANCANI, VINCENZO;GATTINONI, PAOLA;
2015-01-01

Abstract

The forecast of riverbed profile changes is very important for analysing the dynamic evolution of slopes, because it represents the result of the main geomorphological processes. The aim of this paper is to expose a method for predicting sediment transport with a semi-quantitative approach, representing how streambed evolves over time. The predictive model has been implemented through Hec-Ras software, combining an empirical equation [1] both for flow and sediment transport, in order to have a framework to approach the problem of streambed evolution, based on the knowledge of: of climatic features, sediment inflow and river flow rate. Streambank geometric characteristics (i.e., bank heights, slopes, and grain size distribution) have been considered during the modeling procedure. Therefore, the method has been applied to a case study, the Anza River in Piemonte (Northern Italy), to test the model. The Anza River includes a reservoir where can be evaluated the accumulation of sediment. The changes of the riverbed profile calculated showed a massive deposition of gravels and sands, bringing about an upward displacement of the apex of the sedimentation area. A similar behavior was also observed in other catchment basins in mountain areas (e.g. in the basin of the Tartano River in Valtellina, Lombardy). Moreover, the results are comparable with the data on the sediments accumulated in the reservoir, demonstrating that the method might be useful in dealing with the problem and that it is potentially widely applicable. Nevertheless, it still needs to be independently tested in different regions. At this aim, the preliminary knowledge, for each section of the river, about the solid materials inflow and the river discharge are useful for a correct calculation of the riverbed profile change.
2015
International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM
978-619-7105-32-2
numerical modeling, sediment transport, landslide
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/968739
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