Measuring Annual Sedimentation through High Accuracy UAV-Photogrammetry Data and Comparison with RUSLE and PESERA Erosion Models

Abstract

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.

Monitoring and Quantifying Soil Erosion and Sedimentation Rates in Centimeter Accuracy Using UAV-Photogrammetry, GNSS, and t-LiDAR in a Post-Fire Setting

“…Optimal study sites are areas of limited or no vegetation. These sites relate to post-fire settings, settings controlled by overgrazing [111][112][113][114][115][116][117][118], or areas of high sedimentation, where eroded, transported sediments constantly cover the recently formed vegetation (as at the Platana test site [47]). To our knowledge, no detailed soil erosion investigation has yet been conducted regarding the combination of UAV-and t-LiDAR-derived point cloud algorithms in fire-affected areas.…”

“…There has been a surge of interest in the Unmanned Aerial Vehicle (UAV) Structure from Motion (SfM) data collection technique, primarily driven by the cost-effectiveness of the equipment and the enhanced speed of data acquisition. This method, combined with recent advancements in computer technology, has positioned photogrammetry as a robust tool for geomorphological research [47]. Applications across various domains, such as monitoring riverbed topography [48][49][50][51], riverbank analysis [52,53], erosion [38,[54][55][56][57], landslides [58], erosion rate assessment [59][60][61][62][63][64], coastal analysis [65], and rockfall/rock slope stability analysis [66], have significantly expanded the realm of geomorphological analysis.…”

Soil erosion effects and mechanisms in the karst peak-cluster depression area from a multi-scale landscape perspective

“…UAV technology has been successfully employed in soil erosion monitoring studies, and Sebastian et al (2012) were among the pioneers in utilizing UAVs to create high-precision DTMs and orthoimages to achieve superior monitoring outcomes. Furthermore, Alexiou et al (2023) demonstrated the utility of high-resolution UAV imagery in measuring sediment deposition in a typical Mediterranean watershed. The high level of detail and spatial resolution offered by UAV imagery enable the identification and characterization of fine-scale landscape features related to soil erosion, leading to more accurate assessments of the soil erosion distribution and patterns compared to traditional methods such as satellite imagery and ground-based surveys.…”