The morphodynamic depth of closure, signifies the depth at which fluid motion is unable to move sediment, and morphological change ceases. A very timely contribution from Ortiz et al (2016) expresses depth of closure as a function of both wave climate and a time scale of interest. At IRESS 2017, I presented a quick first-pass applying Ortiz’s model and adopting their workflow for application to the Texas coast using Army Corps of Engineers’ WIS hindcast information and the Coastal Relief Model from NOAA. Although Ortiz’ model does not do well to describe the rather tranquil wave climate of the Texas coast, the results show that fair weather wave base is typically above 4 m water depth, and may increase in depth slightly from the Upper Texas coast to the Lower Texas coast. These predictions crudely agree with depth profiles of morphological change estimated by differencing sequential shoreface profiles obtained by Texas A&M University Corpus Christi which are available from their Coastal Habitat Restoration GIS website. Click on the picture of the poster to download a PDF copy.
 Ortiz, A. C., and A. D. Ashton (2016), Exploring shoreface dynamics and a mechanistic explanation for a morphodynamic depth of closure, J. Geophys. Res. Earth Surf.,121,442–464, doi:10.1002/2015JF003699. (PDF link)
Aeolian dune topography arises from a highly non-linear interaction between sediment transport, topography, and boundary shear stress. To explore the growth of aeolian dunes under a variety of boundary conditions, a new surface model for aeolian bedform topography is adapted from a surface model of subaqueous bedform topography (Jerolmack and Mohrig, 2005). The resulting modeling framework approximates the dynamic motions of aeolian bedform topography driven by bedform field boundary conditions; namely, different distributions of sediment transport direction and investigating bedform growth with and without the constraint of a fixed sediment source area (modeled as a fixed elevation boundary). The rates at which modeled aeolian bedforms grow and morphologically mature are found to be highly sensitive to the chosen boundary conditions. Click on the image of the manuscript header to visit the journal’s website and read more about this study.
The videos below show four permutations of two boundary conditions: uni- and bi-modal distributions of sediment transport direction are used to grow bedform topography with and without the constraint of a sediment source area. In these videos hot colors indicate higher topography and cooler colors indicate lower topography.
Uni-modal distribution of sediment transport direction with periodic boundaries
Uni-modal distribution of sediment transport moving sediment from a fixed source
Bi-modal distribution of sediment transport direction with periodic boundaries
Bi-modally distributed sediment transport moving sediment from a fixed source
The aeolian bedform surface model code is malleable and readily modified for exploratory study of bedform topography that inherits morphological traits from aeolian bedform field boundary conditions. A version of the source code for these simulations is available from MATGEO. However, a newer version of this software will be made available via a public repository on GitHub, shortly.
 Jerolmack DJ, Mohrig D (2005) A unified model for subaqueous bed form dynamics. Water Resour Res 41(12):W12421. doi:10.1029/2005WR004329 (PDF link)
Aeolian dune motion is thought to be driven by an annual cycle of sediment-transporting wind events. Each wind event drives uneven motion of dune crestlines, yet dune crestlines align as a trend to an annual cycle of wind . Understanding the variability in dune motion over such a cycle aids the interpretation of aeolian cross-stratification, often available only in the limiting exposure of core and outcrop.
Digital elevation models obtained by light detection and ranging (lidar, Fig. 1) are used to estimate dune brink motion and sediment flux along the sinuous crestlines of crescentic dunes at White Sands gypsum dune field (south-central New Mexico, USA) over an annual cycle of wind.
- Fig. 1 Time lapse animation of dune elevation of study area within White Sands, NM. Duration is approximately 3 yrs.
By using an edge detection algorithm, dune brink motion (Fig. 1) can be used to estimate local values of sediment flux. These estimations reveal that dune motion and sediment flux are very well described by a circular normal distribution when sampled using a spatial window of approximately the size of six average dunes. At this scale, the distribution of erratic dune motion is symmetrically distributed around the average lee surface dip direction. Therefore, uneven motion of dune crest lines offset, and the geometric self-organization of dune crests as a trend line is maintained.
- Fig. 2 Dune brink movement occurring over slightly more than a year is shown by the colormapped circles. The elevation of the aeolian dunes is shown by the grayscale.