Land Degradation Assessment in an Olive Orchard Using Different Soil Erosion Estimation Methods

Land degradation caused by soil erosion is a major challenge in Mediterranean sloping agroecosystems, where extreme weather events and conventional land management practices accelerate soil loss and threaten long-term sustainability. This study evaluates and compares three complementary approaches to estimate soil erosion in an olive orchard in Messenia, Greece. Field-based runoff plots provided direct measurements of sediment yield, drone-based Light Detection and Ranging (LiDAR) surveys enabled soil surface change detection through the Difference of Digital Elevation Models (DoD) method, and the Revised Universal Soil Loss Equation (RUSLE) was applied to model erosion risk using site-specific parameters. Results indicate that field measurements and RUSLE estimates are broadly consistent, particularly when the model is calibrated with empirical data, offering reliable insights into soil loss dynamics. In contrast, the LiDAR-DoD analysis identified patterns of soil surface displacement, which reflected spatial variation in surface change across the olive orchard. Overall, the integration of field monitoring, remote sensing, and modeling highlights the strengths and limitations of each method and demonstrates the value of multi-method approaches for improving erosion assessment and supporting sustainable land management in vulnerable Mediterranean landscapes.