Comparison of Methods for Determining Erosion Threshold of Cohesive Sediments Using a Microcosm System

Erosion of cohesive sediments is a ubiquitous phenomenon in estuarine and intertidal environments. Several methods have been proposed to determine the surface erosion threshold (τc0), which are still debatable because of the numerous and uncertain definitions. Based on erosion microcosm experiments, we have compared three different methods using (1) eroded mass (EM), (2) erosion rate (ER), and (3) suspended sediment concentration (SSC), and suggested a suitable method for revealing the variation of erodibility in intertidal sediments. Erosion experiments using a microcosm system were carried out in the Muuido tidal flat, west coast of South Korea. The mean values of τc0 for three methods were: 0.20 ± 0.08 Pa (EM); 0.18 ± 0.07 Pa (ER); and (3) 0.17 ± 0.09 Pa (SSC). The SSC method yielded the lowest τc0, due to the outflow of suspended sediment from the erosion chamber of the microcosm. This was because SSC gradually decreased with time after depleting the erodible sediment at a given bed shear stress (τb). Therefore, the regression between SSC and applied τb might skew an x-intercept, resulting in the underestimation (or “not-determined”) of τc0. The EM method yielded robust and accurate (within the range of τb step at which erosion begins) results. The EM method represents how the erodible depth thickens as τb increases and therefore seems better suited than the SSC and ER methods for representing depth-limited erosion of cohesive sediments. Furthermore, this study identified the spatiotemporal variations of τc0 by EM method in an intertidal flat. The τc0 in mud flat was about two times higher than that in mixed flat. Compared to the end of tidal emersion, the sediment was 10–40% more erodible at the beginning stage.

Critical Shear Stress for Erosion of Sand-Mud Mixtures and Pure Mud

The erosion threshold of sand-mud mixtures is investigated by analyzing the momentum balance of a sand particle or a mud parcel in the mixture bed surface, and a formula for the critical shear stress of sand-mud mixtures is developed, which also applies for pure sand and mud. The developed formula suggests that the variation of the critical shear stress of sand-mud mixtures over mud content is mainly caused by the varying dry bulk density of the mud component in the mixture. The developed formula reproduces well the variation of the critical shear stress of sand-mud mixtures over mud content and can predict the critical shear stress of both sand-mud mixtures and pure mud in the process of consolidation. The developed formula promises to be convenient for application by relating the critical shear stress to mud content and the dry bulk density of sediment.

The Impacts of Climate Variability on the Wind Erosion Potentials in the Western Region of Makran Coastal Plain, Iran

Coastal plains are prone to various degrees of wind erosion due to their characteristics. This study aimed to investigate the effect of climatic factors in the western region of Makran coastal plain in a southeastern region of Iran on the wind erosion potential. The study period was 1993-2018. First, the data related to wind velocities, relative humidity and precipitation, and the granulometric data of plain surface sediments were obtained. Then, the wind erosion threshold velocity in humid air conditions was determined. Finally, the Mann-Kendall test was applied to analyze the probability of wind erosion and its temporal variability. The results indicated that the wind erosion threshold, in terms of humidity changes, varied from 7.21 to 12.31 meters per second during the study period. The highest probability of wind erosion was in February, March, and April, with 24.69%, 21.51%, and 20.41%, respectively. The lowest probability of wind erosion was in October, November, and September with 4.00%, 4.12%, and 6.00%, respectively. Finally, the erosion trend analysis indicated that wind erosion was a temporal phenomenon that increased significantly in January (winter solstice) and July (summer solstice). These months were characterized by an increase in the wind blowing at speed above the threshold. Otherwise, the months were not different from other months of the year in terms of precipitation or the number of dry days. Therefore, wind erosion is expected to maximize in the early winter and the early summer.

Retrieving the global distribution of the threshold of wind erosion from satellite data and implementing it into the Geophysical Fluid Dynamics Laboratory land–atmosphere model (GFDL AM4.0/LM4.0)

Dust emission is initiated when surface wind velocities exceed the threshold of wind erosion. Many dust models used constant threshold values globally. Here we use satellite products to characterize the frequency of dust events and land surface properties. By matching this frequency derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol products with surface winds, we are able to retrieve a climatological monthly global distribution of the wind erosion threshold (Vthreshold) over dry and sparsely vegetated surfaces. This monthly two-dimensional threshold velocity is then implemented into the Geophysical Fluid Dynamics Laboratory coupled land–atmosphere model (AM4.0/LM4.0). It is found that the climatology of dust optical depth (DOD) and total aerosol optical depth, surface PM10 dust concentrations, and the seasonal cycle of DOD are better captured over the “dust belt” (i.e., northern Africa and the Middle East) by simulations with the new wind erosion threshold than those using the default globally constant threshold. The most significant improvement is the frequency distribution of dust events, which is generally ignored in model evaluation. By using monthly rather than annual mean Vthreshold, all comparisons with observations are further improved. The monthly global threshold of wind erosion can be retrieved under different spatial resolutions to match the resolution of dust models and thus can help improve the simulations of dust climatology and seasonal cycles as well as dust forecasting.