Restoration resources are usually limited and strategic information on and erosion susceptible areas are required to avoid further degradation. This study has potential in the Mzimvubu River Catchment, South Africa, where two large reservoirs are planned on the Tsitsa tributary. The Tsitsa River Catchment, however, consists of highly erodible soils with widespread gully erosion evident. It is important to prevent further gully erosion in the catchment due to the presence of duplex and dispersive soils. Therefore, this study modelled areas that are susceptible to gully development in the Tsitsa River Catchment, as well as estimated the sediment yield potential from the susceptible areas if gully development occurs. This was achieved by mapping gully-free areas in a GIS that have the same DEM-derived topographical variables, soil associations and land cover as gullied areas, followed by scenario analysis of the potential sediment yield. More than 30 000 ha (7%) of the catchment is intrinsically susceptible to further gully development, consisting of drainage paths with a large contributing area and erodible duplex soils. If not protected, these susceptible areas could contribute an additional 300 million m³ of sediment to the river network, reducing the volumes of both reservoirs by more than 50%.

Gully erosion can reach alarming dimensions, and in several cases contributes significantly to soil loss and sediment yield in catchments. The studied example is one of the largest known gully networks in the world (its surface area is approximately 0.5 million m² and volume 5 million m³), more than twice as large compared to the largest gullies described in peer-reviewed literature. To improve gully management strategies, it is not only critical to understand the factors that lead to erosion, but also to identify the extent of in-channel erosional and depositional features. Few studies consider in-channel patterns of erosion and deposition within gully systems. This study utilises a fixed-wing Unmanned Aerial Vehicle (UAV) and Structure-from-Motion (SfM) photogrammetry to create a high resolution orthomosaic and Digital Surface Model (DSM) to determine the position and spatial extent of erosional and depositional features within a large gully network in South Africa. Formation of such a large gully in relation to a relatively small drainage area is unusual but can be explained by the presence of dispersive soils and regional landscape incision. Longitudinal and cross-sectional profiles indicate that the gully network consists of three channel types (i.e. V-shaped, U-shaped and trapezoidal), each with a unique combination of erosional and depositional features. This study demonstrates the value of identifying and mapping of intra-gully features to better understand sediment transfer within the gully network to implement appropriate restoration strategies, which in this instance should focus on depositional zones to enhance channel decoupling.

Soil erosion has been identified as an issue in South African farming for more than a century. Erosion of land surfaces by water or wind is a natural process which might be accelerated directly by human impact on land surface properties, e.g., vegetation and soils. An assessment of soil erosion risk indicates average soil loss rates two orders of magnitude larger than long-term soil formation rates. This challenging condition clearly underlines the need for continuous application of established policies and principles as well as emerging modes of conservation agriculture in farming activities in most parts of South Africa. In addition, conservation agriculture has been shown to have positive effects on the cost–value ratio, but diffusion and adoption of this innovative approach still meet resistance often founded in traditional faith and belief systems. However, to cope with challenges from global climate change, e.g., intensified extreme weather conditions (droughts and flooding), strengthened resilience of farming systems is required to i) meet increased domestic and global demand for food and ii) to put into practice sustainable management to diminish on-site and off-site damages from soil erosion on the way to reach sustainable development goals.

Landslide mapping is essential for hazard assessment and mitigation efforts, with remote sensing techniques offering valuable tools for detecting and monitoring changes in land cover associated with landslide events. In this study, a pixel-based change detection approach with fuzzy membership functions was employed to map landslide scars in both the Pinetown and Port St. Johns areas of South Africa. Covariates including the Normalized Difference Vegetation Index (NDVI), slope, and Vertical Distance to Channel Network (VDCN) were selected to detect changes in land cover indicative of landslide occurrence. High-resolution satellite imagery from PlanetScope (3 m) was utilized to capture small-scale landslide features, enhancing the accuracy of the mapping process. Results from the calibration area (Pinetown) have a Kappa value of 0.60, F1 score of 0.93, and an overall accuracy of 0.88, whereas extrapolation areas (Port St. Johns) resulted in a Kappa value of 0.70, F1 score of 0.95, and an overall accuracy of 0.92%. Challenges such as spatial incoherence and over-detection were encountered, highlighting the need for careful interpretation and refinement of the mapping approach. Extrapolation of the pixel-based change detection method from the Pinetown to the Port St. Johns area revealed limitations associated with differences in land use practices, surface cover, and availability of satellite imagery. Despite these challenges, the approach detected additional landslide occurrences in both study areas. Overall, this study demonstrates the effectiveness of pixel-based change detection with fuzzy membership functions for mapping landslide scars in diverse settings.