Predicting rainfall kinetic energy under forest canopies—A pilot study using ULS

Rainfall erosivity, expressed in kinetic energy, is determined by intensity, velocity and drop size distribution. In natural precipitation, these properties vary and can be substantially altered by the vegetation before reaching the ground. The splash effect of impacting raindrops on the soil surface can initiate soil erosion. While research in this regard has focussed on relating plant characteristics to erosion processes, there is a lack of studies that attempt to reverse this by predicting throughfall kinetic energy from plant properties. This has been attempted by the Vegetation Splash Factor (VSF), a model solely based on the three‐dimensional distribution of vegetation surfaces derived from forest lidar forest data. We conducted a pilot study using the VSF model to validate it with in situ measurements and confirm its general suitability. We found a significant correlation between the observed and predicted effect of vegetation on the kinetic energy of rainfall, which demonstrates the suitability of the VSF, despite being solely based on structural traits. The observed effect of vegetation on rainfall kinetic energy exceeded literature reports, leading to systematic underestimation by the model. Our results showed that the VSF can be used to spatially continuously predict the effect of vegetation on the erosivity of rainfall from high‐resolution lidar data. These findings open new possibilities for research on splash erosion under vegetation, shifting the perspective from point‐based studies towards area‐wide approaches. The simplicity of the approach facilitates adaptation for wider use. The first application of the VSF in a field study has proved that the concept is functional and can illustrate zones of increased potential for soil loss under full vegetation cover. This adds to the methodological tool box for erosion studies and can support decision‐makers in forestry and agriculture in the future.