Geomorphometry for studying the evolution of small basins: an example in the Italian Adriatic foredeep

TitleGeomorphometry for studying the evolution of small basins: an example in the Italian Adriatic foredeep
Publication TypeBook Chapter
Year of Publication2015
AuthorsCoco, Laura, Viviana Cestrone, and Marcello Buccolini
Secondary AuthorsJasiewicz, Jaroslaw, Zbigniew Zwoliński, Helena Mitasova, and Tomislav Hengl
Book TitleGeomorphometry for Geosciences
Pagination107 - 110
PublisherBogucki Wydawnictwo Naukowe, Adam Mickiewicz University in Poznań - Institute of Geoecology and Geoinformation
CityPoznań, Poland
ISBN Number978-83-7986-059-3
Abstract

The present work focused on the influence of pre-erosion slope morphometry on the arrangement and evolution of small basins in the Periadriatic belt of central Italy. MSI (Morphometric Slope Index) was considered as general index for slope morphometry and tested as geomorphometric driver of fluvial erosion processes. Using two DEMs with different resolution (30 m cell-size ASTER Global DEM and 10 m cell-size Italian TINITALY DEM) and TauDEM toolbox within ArcGIS, we automatically extracted watersheds and stream networks. We firstly proved their validity through visual investigation and statistics, and analyzed the effect of the different resolution on the morphometric parameters. Subsequently, we analyzed the influence of MSI on both drainage network and eroded volume through Regression Analysis and t- Student Statistics using the DEM which was proved to be the most correct. We reached the following main outcomes: (i) the slope morphometric features combined in MSI strongly influenced the amount of eroded material since the inception of fluvial erosion process, (ii) the drainage density was linked to MSI by a logarithmic trend, and (iii) this relation directly depended on lithological features of the basins due to different lithotechnical behavior of clay and conglomerate on which they were set. We proposed a further advancement of this research focused on geomorphological hazards, considering MSI as predictor, e.g., of landslides, and developing a model for landslides susceptibility.

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