Search

Model-based soil erosion studies have increased in number, given the availability of geodata and the recent technological advances. However, their accuracy remains rather questionable since the scarcity of field records hinders the validation of simulated values. In this context, this study aims to present a method for measuring sediment deposition at a typical Mediterranean catchment (870 ha) in Greece through high spatial resolution field measurements acquired by an Unmanned Aerial Vehicle (UAV) survey. Three-dimensional modeling is considered to be an emerging technique for surface change detection. The UAV-derived point cloud comparison, applying the Structure-from-Motion (SfM) technique at the Platana sediment retention dam test site, quantified annual topsoil change in cm-scale accuracy (0.02–0.03 m), delivering mean sediment yield of 1620 m3 ± 180 m3 or 6.05 t ha−1yr−1 and 3500 m3 ± 194 m3 or 13 t ha−1yr−1 for the 2020–2021 and 2021–2022 estimation. Moreover, the widely applied PESERA and RUSLE models estimated the 2020–2021 mean sediment yield at 1.12 t ha−1yr−1 and 3.51 t ha−1yr−1, respectively, while an increase was evident during the 2021–2022 simulation (2.49 t ha−1yr−1 and 3.56 t ha−1yr−1, respectively). Both applications appear to underestimate the net soil loss rate, with RUSLE being closer to the measured results. The difference is mostly attributed to the model's limitation to simulate gully erosion or to a C-factor misinterpretation. To the authors' better knowledge, this study is among the few UAV applications employed to acquire high-accuracy soil loss measurements. The results proved extremely useful in our attempt to measure sediment yield at the cm scale through UAV-SfM and decipher the regional soil erosion and sediment transport pattern, also offering a direct assessment of the retention dams' life expectancy. [ABSTRACT FROM AUTHOR]

Mediterranean ecosystems are commonly vulnerable to wildfires. Accelerated erosion processes due to wildfires in those environments constitute a major restrictive factor in their sustainability. This study aims at evaluating the use of the Revised Universal Soil Loss Equation (RUSLE) and the Pan-European Soil Erosion Risk Assessment (PESERA) models in predicting the changes in spatial variability of soil erosion following a wildfire event. A site in Greece on which a wildfire occurred in the summer of 2007 is used as a case study. Soil erosion rates for the site before and after the fire outbreak were estimated by the two models. Inputs for both models included climatic, land-use, soil type, topography, Earth Observation (EO) as well as management and other ancillary data. Both models showed a substantial increase of soil erosion rates in the affected area as a result of the fire, particularly towards the steeper slopes and on areas of high burning severity. Yet, there were noticeable differences in the predictions between the 2 models in terms of absolute estimates of soil erosion rates before and after the fire event. Mean pre-fire erosion rates from RUSLE were ~ 2.5 times higher than those from PESERA. RUSLE predicted considerably higher mean erosion in comparison to PESERA for the post-fire conditions, yet of much less spatial variability. Average post-fire soil loss value, compared to pre-fire, was about nine and six times greater when using the RUSLE and the PESERA model respectively. RUSLE predictions were most sensitive to topographic and rainfall erosivity factors. PESERA showed high sensitivity to the vegetation coverage as well as to the soil characteristics inserted as crusting and erodibility variables. To our knowledge, this is the first study performing an intercomparison of soil erosion rate predictions between these two models, particularly so in the context of the influence of wildfire events. This study provides a key contribution towards our ability to better understand the effect of fire on soil erosion in the Mediterranean and elsewhere, as well as the ability of those widely used models as efficient tools to be used for this purpose. The latter is of key significance and practical value for research and policy decision making purposes alike, where information on spatiotemporal estimates of soil erosion rates may be required. [ABSTRACT FROM AUTHOR]