Dust emission source characterization for visibility hazard assessment on Lordsburg Playa in Southwestern New Mexico, USA

A field study of the surface disturbance effects of animals and motor vehicles on aeolian sediment emission from a silty playa surface

Dry playa surfaces can be extremely vulnerable to disturbance which breaks their surface crusts resulting in increased aeolian sand and dust emissions. Trampling by livestock and motor vehicles is an important source of this disturbance. The Hamoun Lakes in the Sistan region of Iran are a major source area of dust storms which are causing damage to infrastructure and communities. This study performed portable wind tunnel tests of controlled surface disturbance by animals (cow, sheep) and motor vehicles (automobile, motorcycle) on a silty playa surface of Hamoun Saberi lake. The aim of this study was to assess the effect of different levels of trampling and disturbed surfaces by both vehicles and livestock on dust emission at wind speeds of 6 and 12 m s^-1. A significant increase of sediment emission was found with increased number of passes of vehicles and livestock and the degree of surface disturbance, more so at the high wind speed (12 m s^-1). No significant differences were observed between a 10-20% disturbance level and an undisturbed surface, but statistically significant differences became apparent when disturbances reached 50-60% to 90-100% compared to undisturbed surfaces. Greater emission rates were reached by disturbances provided by automobile and cow compared to motorcycle and sheep, indicating greater trampling effects of automobile and cow likely related to greater weight and larger footprint. The automobile was the most surface-destructive of the four anthropogenic disturbances, providing emission in a lower number of passes compared to the motorcycle, cow and sheep. Better management of vehicle and livestock allocation on playas subject to disturbance, such as the Hamoun Lakes, will be a useful strategy to reduce disturbance and the frequency and intensity of dust storms.

Combining Optical and Radar Satellite Imagery to Investigate the Surface Properties and Evolution of the Lordsburg Playa, New Mexico, USA

Driven by erodible soil, hydrological stresses, land use/land cover (LULC) changes, and meteorological parameters, windblown dust events initiated from Lordsburg Playa, New Mexico, United States, threaten public safety and health through low visibility and exposure to dust emissions. Combining optical and radar satellite imagery products can provide invaluable benefits in characterizing surface properties of desert playas—a potent landform for wind erosion. The optical images provide a long-term data record, while radar images can observe land surface irrespective of clouds, darkness, and precipitation. As a home for optical and radar imagery, powerful algorithms, cloud computing infrastructure, and application programming interface applications, Google Earth Engine (GEE) is an invaluable resource facilitating acquisition, processing, and analysis. In this study, the fractional abundance of soil, vegetation, and water endmembers were determined from pixel mixtures using the linear spectral unmixing model in GEE for Lordsburg Playa. For this approach, Landsat 5 and 8 images at 30 m spatial resolution and Sentinel-2 images at 10–20 m spatial resolution were used. Employing the Interferometric Synthetic Aperture Radar (InSAR) techniques, the playa’s land surface changes and possible sinks for sediment loading from the surrounding catchment area were identified. In this data recipe, a pair of Sentinel-1 images bracketing a monsoon day with high rainfall and a pair of images representing spring (dry, windy) and monsoon seasons were used. The combination of optical and radar images significantly improved the effort to identify long-term changes in the playa and locations within the playa susceptible to hydrological stresses and LULC changes. The linear spectral unmixing algorithm addressed the limitation of Landsat and Sentinel-2 images related to their moderate spatial resolutions. The application of GEE facilitated the study by minimizing the time required for acquisition, processing, and analysis of images, and storage required for the big satellite data.