Elisa Marras

The mitigation of the risk from gravitational natural hazards involves a variety of measures in engineering and management. The basis for any measures is the identification of hazard prone areas by considering past events and model simulations. Various models are available for the simulation of gravitational natural hazards but their application is often a trade off between simplicity and accuracy. A physical interpretation of the well established energy line principle allows to formulate the corresponding equations of motion and to introduce a model that is still simple but more accurate. The equations of motion are derived by the application of the Lagrange formalism for a friction block that slides on an inclined plane. Furthermore, a numerical algorithm based on the Euler method is set up to solve the equations of motion on a digital terrain model. This model is applied and compared to the energy line principle based on the equation of energy and to past events in two case studies for rockfall and landslide. The outcomes show that the formulation of the energy line principle with the equations of motion corresponds well to the formulation based on the equation of energy but allows a more differentiated simulation of the runout zone that reproduces better the past events. However, there are artifacts from the numerical solution of the equations of motion that require a deeper theoretical investigation and also uncertainties in the past events that must be worked through in a more elaborated empirical study. Nevertheless, the concept of this approach to enhance the performance of the energy line principle simply by another perspective to the same physical concept is thus proved.

Accurately identifying hazard-prone areas is critical for mitigating risks from gravitational natural hazards such as landslides and rockfalls. Although many models exist to simulate these rapid mass movements, there are often trade-offs between simplicity, robustness and precision. This study builds upon the well-established energy line principle by reinterpreting the energy line angle as a kinetic friction coefficient, enabling the derivation of equations of motion that describe the forces driving mass movements. Using the Lagrange formalism for a sliding friction block, the equations of motion are developed and solved numerically with an Euler-based algorithm applied to digital terrain models. This force-based perspective retains the energy line principle’s simplicity and robustness while offering improved accuracy. In this study, the method is evaluated using two case studies with 36 documented landslide and 6 rockfall events in northern Italy. The results were compared with those of a traditional energy-based approach as well as with documented past events. The refined model produces smaller, more differentiated runout zones, achieving 41% resp. 11% higher true positive and 65% resp. 16% lower false positive rates compared to the energy-based approach for reproducing the past rockfall and landslide events. These findings demonstrate that the developed approach enhances accuracy without increasing computational complexity. This enhancement has the potential to extend the application of the energy line principle beyond preliminary analyses, enabling more detailed and reliable hazard mapping at larger spatial scales.

Incident gross precipitation is divided by tree canopies into three main parts: i) intercepted rainfall, which evaporates directly from the canopies, ii) throughfall, which reaches the soil surface after passing through the canopies, and iii) stemflow, which is concentrated from the canopies to the stems. Stemflow tends to infiltrate preferentially around the base of the stem, and once belowground, is channeled by tree roots.The objective of this research was to investigate the contribution of stemflow and throughflow to subsurface water dynamics in a hillslope forested with beech trees. The experimental activities were carried out in a 10 x 10 m plot located in the Lecciona catchment of the Appennine Mountains, Central Italy. Stemflow was collected from seven beech trees located within the plot. Stemflow and throughfall were sequentially and then simultaneously induced using controlled water applications. Time-lapse ground-penetrating radar (GPR) surveys were conducted under each line of trees. Overland flow and subsurface runoff were collected with V-shaped gutters positioned at the bottom of the trees and at the downhill plot edge.Stemflow infiltration rates were calculated by a mass balance, i.e., subtracting the collected overland flow from the injected volume and then dividing by the stem basal area and the time of steady infiltration. Mean values for each tree and for the entire plot, the latter considering the throughfall experiments, were approximately 1000 mm/h. The GPR data enabled the detection of active preferential flow paths, assessment of hillslope connectivity, and estimation of flow velocities. GPR gave relevant information in the flow pathways in the soils, the effects of root systems and its combination with matrix flow.This experiment represents a straightforward, replicable, and non-invasive method for characterizing the role of trees in water runoff and infiltration at the hillslope spatial scale, and more broadly, in understanding how forested hillslope respond to rainstorms.

The hydrological response of steep slopes catchments is strongly conditioned by the connectivity of subsurface preferential flows. The objective of this research is to investigate the role played by stemflow infiltration in subsurface water flow dynamics, focusing on a forested hillslope located in an Aleppo pine Mediterranean forest (Pinus halepensis, Mill.) located at Sierra Calderona, Valencia province, Spain. We combined stemflow artificial experiments with ground-penetrating radar (GPR) techniques as a non-invasive method to investigate stemflow-induced preferential flow paths activated by different trees and the related hydrological connectivity at the hillslope scale. Our observations allowed us to identify different dynamics associated with the initiation of stemflow and then lateral preferential flow, including the activation of connected preferential flow paths in soils that received stemflow water from different trees. These observations provided empirical evidence of the role of stemflow in the formation of lateral preferential flow networks. Our measurements allow estimations of flow velocities and new insight on the magnitude of stem-induced lateral preferential flow paths. The applied protocol offers a simple, repeatable and non-invasive way to conceptualize hillslope responses to rainstorms.