Abstract

Rill erosion, mostly affecting steep and long hillslopes, is one of the most severe effects of deforestation and wildfires in natural ecosystems. Specific monitoring and accurate but simple models are needed to assess the impacts of these forest disturbances on the rill detachment process. To address this need, this study has simulated the rill detachment capacity (Dc) through flume experiments on samples of soils collected in hillslopes after deforestation and severe burning. The associations between Dc and organic matter (OM) and the aggregate stability of soil (WSA), two key parameters influencing the rill detachment process, have also been explored under the two soil conditions (deforested and burned soils) using multivariate statistical techniques. Finally, linear regression models to predict Dc from these soil parameters or the hydraulic and morphological variables (water flow rate, WFR, and soil slope, S), set in the flume experiments, have been proposed for both soil conditions. Higher Dc in samples from deforested sites compared to the burned soils (+35%) was measured. This Dc increase was associated with parallel decreases in OM (−15%) and WSA (−34%) after deforestation compared to the wildfire-affected sites. However, the discrimination in those soil properties between the two soil conditions was not sharp. Accurate linear equations (r2 > 0.76) interpolating Dc and the shear stress (τ) have been set to estimate the rill erodibility (Kr) to evaluate soil resistance in erosion models to be applied in deforested or burned sites.

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