Arid and semi-arid landscapes often show a patchwork of bare and vegetated spaces. Their heterogeneous patterns can be of natural origin, but may also indicate soil degradation. This study investigates the use of unmanned aerial vehicle (UAV) imagery to identify the degradation status of soils, based on the hypothesis that vegetation cover can be used as a proxy for estimating the soils’ health status. To assess the quality of the UAV-derived products, we compare a conventional field-derived map (FM) with two modelled maps based on (i) vegetation cover (RGB map), and (ii) vegetation cover, topographic information, and a flow accumulation analysis (RGB+DEM map). All methods were able to identify areas of soil degradation but differed in the extent of classified soil degradation, with the RGB map classifying the least amount as degraded. The RGB+DEM map classified 12% more as degraded than the FM, due to the wider perspective of the UAV compared to conventional field mapping. Overall, conventional UAVs provide a valuable tool for soil mapping in heterogeneous landscapes where manual field sampling is very time consuming. Additionally, the UAVs’ planform view from a bird’s-eye perspective can overcome the limited view from the surveyors’ (ground-based) vantage point.

The use of sediment settling velocity based on mineral grain size distribution in erosion models ignores the effects of aggregation on settling velocity. The alternative approach, wet-sieved aggregate size distribution, on the other hand, cannot represent all destructive processes that eroded soils may experience under impacting raindrops. Therefore, without considering raindrop impact, both methods may lead to biased predictions of the redistribution of sediment and associated substances across landscapes. Rainfall simulation is an effective way to simulate natural raindrop impact under controlled laboratory conditions. However, very few methods have been developed to integrate rainfall simulation with the settling velocity of eroded sediment. This study aims to develop a new proxy, based on rainfall simulation, in order to identify the actual settling velocity distribution of aggregated sediment. A combined Raindrop Aggregate Destruction Test-Settling Tube (RADT-ST) approach was developed to (1) simulate aggregate destruction under a series of simulated rainfalls; and (2) measure the actual settling velocity distribution of destroyed aggregates. Mean Weight Settling Velocity (MWSV) of aggregates was used to investigate settling behaviors of different soils as rainfall kinetic energy increased. The results show the settling velocity of silt-rich raindrop impacted aggregates is likely to be underestimated by at least six times if based on mineral grain size distribution. The RADT-ST designed in this study effectively captures the effects of aggregation on settling behavior. The settling velocity distribution should be regarded as an evolving, rather than steady state parameter during erosion events. The combined RADT-ST approach is able to generate the quasi-natural sediment under controlled simulated rainfall conditions and is adequately sensitive to measure actual settling velocities of differently aggregated soils. This combined approach provides an effective tool to improve the parameterization of settling velocity input for erosion models.