Soil erosion by water is one of the most widespread forms of soil degradation in Europe. In the current context of global change, a consistent increasing of erosion is expected, principally due to a greater frequency of extreme, localized rainfall events, as predicted by recent climate models. Accelerated erosion, leading to a general degradation of the environment, depletion of soil nutrients, and agricultural areas exploitation, has become a central topic in the environmental research.
These extremes, responsible of dramatic erosion, especially in cultivated areas, have become a real challenge for agriculture and society itself. This has socio-economic repercussions due to the economic loss for damage of crops when they are affected. Awareness of the process and its extent could help stakeholders to define strategies to reduce erosion risk on a spatial dimension that is seldom considered. From society's point of view, communication of the effects during extreme events could help to increase understanding of the risk itself and improve confidence in scientific and technical resources to help people.
Focusing on a Mediterranean region, where these phenomena exist producing muddy floods and catastrophic erosion, this project aims to understand and quantify the effect of extreme rainfall by ground-radar rainfall monitoring and hydrological modelling at regional scale (Tuscany, IT). An integrated modelling approach is developed for a nowcasting-modelling-platform for runoff and soil erosion as support for warning-systems.
A relevant component in examining the effects of extreme rainfall is spatial distribution of the process. For instance, showers generally have a limited spatial extent which take place in a time spanning from few minutes to a half hour. While this dynamic is predominantly responsible for catastrophic events, it is frequently neglected in hydrological and soil erosion modelling because of missing spatial information for precipitation events. To ensure an accurate monitoring of the rainfall events, in this study, we adopted weather ground-radar, one of the most efficient methodologies. The main objective was to model the extreme rainfall events for erosion over the last 10 years with a particular interest directed at the spatial distribution of rainfall events.