PhD. student in Geomorphology at the University of Vienna. His research focuses on landslide hazards, slope hydrology, and dynamic and spatially distributed physically based slope stability modeling.
Received the PhD at the University of Freiburg, Germany in 1992. Since 1993, he is senior researcher and lecturer at the Institute of Geography in Tübingen, Germany. His research deals with the fields of GIS, Climatology, Geomorphology and Geoarchaeology
Post-graduate student of Physical Geography and Landscape System Sciences at University of Tübingen. The focus of his studies is on Geoinformatics, Digital Soil Mapping and Machine Learning.
Obtained his PhD in Geoinformatics and Physical Geography in 2001 at the Friedrich-Schiller-University in Jena, Germany. He is Associate Professor at the University of Pavia in Italy and the Institute of Geography in Tübingen. His expertise lies in the fields of Geoinformatics, Geomorphic Process Modelling, Soil Erosion Assessment, Geoarchaeology and Geophysical Observations.
Extreme meteorological events such as heavy rainstorms are considered to increase due to global warming. The consequences of such events can be manifold, and might cause massive interferences of the hydrological system of a landscape. Particularly the intramontane basins of the Apennine in Italy are frequently threatened by extreme rainfall events that cause severe damage on buildings and infrastructure. Moreover, the lithological and geomorphological settings of these basins, which depict the products of a complex landscape history, amplify these threats. In order to develop possible mitigation strategies, it is crucial to assess landscape functioning by analysing hydrological processes of the landscape system. In this study, we conducted spatially distributed and dynamic hydrological modelling on a catchment in the intramontane basin of the Mugello valley in Tuscany, Italy. Foremost, measurements of saturated hydraulic conductivity and texture analyses were performed to estimate both infiltration and hydraulic conductivity of the surface and topsoil, respectively. We regionalised the collected data with a stochastic gradient treeboost method for the whole catchment. Soil depth was estimated with a simple sine-cosine-slope relation, whereas, hydropedologic parameters for the hydrological model were estimated with pedotransferfunctions applied on the collected infiltration data. We modelled a period of 100 days, representing each day per time step. A synthetic rainfall period was compiled based on measured data from meteorological stations within the Mugello basin. To produce a reliable synthetic rainfall data set, the estimated precipitation values were set in comparison to calculated return periods for extreme events of all available meteorological station. To assess the diversity of the hydrological response of several locations in the catchment, six semirandom test locations were located on hillslopes and spots were sedimentation is apparent. The results show that groundwater and soil moisture fluctuations appear to be significantly different for both hillslopes and areas were sediments are deposited. The differences cannot be explained by the topographical settings but rather by the approximated thickness of the weathered zone and the spatial diversity of the hydropedological properties of the soil.
The authors declare that there are no conflicts of interest present.