Analysis of susceptibility to shallow slope instability for different soil management practices with a probabilistic model approach

In recent decades, climate change has increased slope instability in crop fields and agricultural land; the aim of this research is to identify the most suitable management practices for water retention in Vineyard as well as the less prone to soil erosion and shallow landslides. This study is part of the UNDER-VINE project, the areas of study are located in Oltrepò Pavese, a sector of the northern Appennines in Northern Italy.

In order to identify the proneness of the soils with different management practices (grass cover, legume-based mixture, cereal-based mixture, between and under-the-row mulching) to shallow landslides, the local data concerning several properties of the terrain (soil friction angle, slope angle, soil effective cohesion, root reinforcement provided by plant roots in the soil, soil unit weight, depth below ground level in which a potential sliding surface could develop and suction stress) were collected, field measurements and historical data were also taken into account. After that, the same data were used to calculate the safety factor (SF) formula for every cell of the digital elevation model, with one meter of resolution.

To accomplish that, a probabilistic model has been used, with the realization of a python script that takes for every parameter a value from a given range, than it calculates the SF for every cell. The outcome is a series of raster images showing the variation of the SF within the different sites.

Finally, the model should make it possible to understand which types of land use are most susceptible to slope instability, and whether the different management practices used can lead to a reduction in these phenomena.