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Gully erosion is an environmental problem recognized as one of the worst land degradation processes worldwide. Insight into regional gully perturbations is required to combat the serious on‐ and off‐site impacts of gullying on a catchment management scale. In response, we intersect different perspectives on gully erosion‐specific views in South Africa (SA), a country that exhibits various physiographic properties and spans 1.22 million km2. While the debate surrounding gully origin continues, there is consensus that anthropogenic activities are a major contemporary driver. The anthropogenic impact caused gullying to transcend climatic, geomorphic, and land‐use boundaries, although it becomes more prominent in central to eastern SA. Soil erodibility plays a crucial role in what extent of gully erosion severity is attained from human impact, contributing to the east–west imbalance of erosion in SA. Soil erosion rates from gullying and badlands are limited but suggest that it ranges between 30 and 123 t ha−1 yr−1 in the more prominent areas. These soil loss rates are comparable to global rates where gullying is concerned; moreover, they are up to four orders of magnitude higher than the estimated baseline erosion rate. On a national scale, the complexity of gullying is evident from the different temporal timings of (re)activation or stabilizing and different evolution rates. Continued efforts are required to understand the intricate interplay of human activities, climate, and preconditions determining soil erodibility. In SA, more medium‐ to long‐term studies are required to understand better how changing control factors affect gully evolution. More research is needed to implement and appraise mitigation measures, especially using indigenous knowledge. Establishing (semi)‐automated mapping procedures would aid in gully monitoring and assessing the effectiveness of implemented mitigation measures. More urgently, the expected changes in climate and land‐use necessitate further research on how environmental change affects short‐term gully erosion dynamics. [ABSTRACT FROM AUTHOR]

For many years researchers have linked increases in sediment and bedload from drainage basins to external factors such as increased rainfall. However, natural systems have always shown a high degree of scatter or nonlinearity in this response, which has made prediction of sediment yields difficult. We identify and describe a mechanism for serf-organized criticality in the bedload sediment output from a simple drainage basin evolution model. This implies that identical floods will give considerably different sediment yields, which effectively renders the system unpredictable. Therefore, existing empirical methods for estimating sediment yields may need to be radically reevaluated. Furthermore, sedimentary records used to infer past climate or environmental conditions could simply reflect the internal system dynamics instead of external drivers. doi: 10.1130/G30490.1

Landscape Evolution Models have a long history of use as exploratory models, providing greater understanding of the role large scale processes have on the long-term development of the Earth's surface. As computational power has advanced so has the development and sophistication of these models. This has seen them applied at increasingly smaller scale and shorter-term simulations at greater detail. However, this has not gone hand-in-hand with more rigorous verifications that are commonplace in the applications of other types of environmental models- for example Sensitivity Analyses. This can be attributed to a paucity of data and methods available in order to calibrate, validate and verify the models, and also to the extra complexity Landscape Evolution Models represent - without these it is not possible to produce a reliable Objective Function against which model performance can be judged. To overcome this deficiency, we present a set of Model Functions - each representing an aspect of model behaviour - and use these to assess the relative sensitivity of a Landscape Evolution Model (CAESAR-Lisflood) to a large set of parameters via a global Sensitivity Analysis using the Morris Method. This novel combination of behavioural Model Functions and the Morris Method provides insight into which parameters are the greatest source of uncertainty in the model, and which have the greatest influence over different model behaviours. The method was repeated over two different catchments, showing that across both catchments and across most model behaviours the choice of Sediment Transport formula was the dominate source of uncertainty in the CAESAR-Lisflood model, although there were some differences between the two catchments. Crucially, different parameters influenced the model behaviours in different ways, with Model Functions related to internal geomorphic changes responding in different ways to those related to sediment yields from the catchment outlet. This method of behavioural sensitivity analysis provides a useful method of assessing the performance of Landscape Evolution Models in the absence of data and methods for an Objective Function approach. [ABSTRACT FROM AUTHOR]