Drylands compose more than 40% of Earth’s surface. Although they are found on every continent and are tremendously diverse, a common feature of drylands is sparse vegetation and expanses of bare ground such as soil or sand. In such a context, the wind plays a significant role in moving loose sediments and shaping the landscape.
Understanding the processes of landscape evolution is important for the management of arid and semiarid areas upon which people depend for their livelihoods. But a long-standing problem in drylands research has been quantifying the transport of sediment by wind in the presence of vegetation and how this influences landscape evolution. For example, wind blowing toward a single tree, a cluster of low shrubs, or an expanse of patchy grass will have different effects in terms of the location and severity of erosion and the location and shape of sediment deposition.
However, predicting exactly what will happen is complex because of the range of factors at play. There are natural variables such as the distribution, type, and size of vegetation; the direction, speed, and consistency of wind; and the frequency, duration, and intensity of rainfall. Human influences are also at play, including growing crops on the land, grazing animals, and setting fire to vegetation, all of which change the availability of sediment and the behavior of wind as it passes over the landscape.
Researchers use a wide range of models to simulate what would happen in different conditions, but these models have limitations when scientists try to understand localized variations. Mayaud et al. propose a new approach combining two types of models: those that handle vegetation distribution and those that handle sediment transport. The authors describe the technical aspects of their new Vegetation and Sediment Transport model (ViSTA) and the verification tests carried out. These showed that the model could accurately replicate different physical characteristics of dryland environments at various scales and in response to environmental changes such as fire and grazing.
The next step was to carry out an experiment to test the model. For this the authors chose a particular type of dryland environment, a nebkha dune field. Using empirical field data on rainfall and wind, they compared the landscape evolution generated by the model with measurements at a field site on the Skeleton Coast in Namibia. The size and spacing of landforms produced by the model were found to accurately reflect real features, thus suggesting the promising potential of this model.
Drylands are home to more than 2 billion people worldwide who depend on the environment for their food and livelihoods. However, many dryland environments are suffering from degradation and desertification in the face of multiple pressures, including population increase and pressure on water resources, overfarming and soil depletion, and changing precipitation patterns due to climate change.
As we move toward the end of the United Nations Decade for Deserts and the Fight Against Desertification (2010–2020), this research contributes to a better understanding of dryland landscape processes. The new model is a versatile tool that can be used to simulate a variety of dryland environments and understand the spatial effects of different environmental stresses, whether natural or anthropogenic. (Journal of Geophysical Research: Earth Surface, https://doi.org/10.1002/2016JF004096, 2017)
—Jenny Lunn, Contributing Writer