Research Blog

A new surface model for aeolian dune topography

MatGeoPaper2016Aeolian 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)[1]. 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 However, a newer version of this software will be made available via a public repository on GitHub, shortly.

[1] 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)

Self organization of aeolian dunes

sedimentologyPaperTitle2016Aeolian 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.

Ex-Stream: a program for calculating vertical fluid flux in porous media based on temperature profiles

CAGS2011Temperature is a useful environmental tracer for quantifying movement and exchange of water and heat through and near sediment–water interfaces (SWI). Heat tracing involves analyzing temperature time series or profiles from temperature probes deployed in sediments. Ex-Stream is a MATLAB program that brings together two transient and two steady one-dimensional coupled heat and fluid flux analytical models. The program includes a graphical user interface, a detailed user manual, a practice data set from Swanson and Cardenas (2010)[1], and postprocessing capabilities that enable users to extract fluid fluxes from time-series temperature observations. CAGS2011cProgram output is written to comma-separated values files, displayed within the MATLAB command window, and may be optionally plotted. The models that are integrated into Ex-Stream can be run collectively, allowing for direct comparison, or individually.


Download Ex-Stream software

[1] Swanson, T., and M. Cardenas, 2010, Diel heat transport within the hyporheic zone of a pool-riffle-pool sequence of a losing stream and evaluation of models for fluid flux estimation using heat: Limnology and oceanography, v. 55, p. 1741-1754.

Investigating the hyporheic zone of a pool–riffle–pool sequence using natural heat as a tracer


A pool-riffle-pool sequence is a nearly ubiquitous element of stream bed morphology. The variabiltiy in bed elevation is thought to allow surface water to infiltrate through the stream bed the head of a riffle and upwell back to the stream at the tail of the riffle in a pool-riffle-pool (PRP) sequence, thus driving a surface water-ground water interaction termed hyporheic exchange. Because infiltrating surface water transports heat from daily heating and cooling; Heat tracing within the streambed sediments is a potentially useful method to characterize hyporheic exchange. For this purpose, temperature was monitored within a PRP sequence for several days at Jaramillo Creek in the Valles Caldera National Preserve. Temperature in the hyporheic zone below the pool-riffle-pool sequence reflected the diel temperature change in Jaramillo Creek but not uniformly. The observed thermal pattern exhibited deeper penetration of thermal oscillations below the head pool and shallower penetration below the tail pool. Play the video below to watch diel cycles of temperature change in sediments below a pool-riffle-pool sequence:

To learn more about one-dimensional analytical heat transport (tracing) models that can use such temperature information to estimate the exchange of water between streams and their associated aquifers, check out the manuscript by clicking on the image at the top of this blog post.

Poster presentation: Evaluating heat tracing models in a pool-riffle-pool sequence, GSA Portland 2009

gsaPoster2009A pool-riffle-pool sequence in streambed morphology is thought to drive hyporheic downwelling near the head of the riffle and upwelling at the tail of the riffle and head of the lower pool. Heat tracing is a potentially useful method to characterize these hyporheic flow paths. A pool-riffle-pool sequence within Jaramillo Creek, Valles Caldera National Preserve, New Mexico was instrumented with a two dimensional vertical array of thermistors during the summers of 2008 and 2009. Three one-dimensional analytical heat transport models (Hatch et al 2006, Keery et al 2007, and Schmidt et al 2007) were used to individually interpret sections of the pool-riffle-pool sequence to quantify vertical fluid fluxes. The modeled fluxes were then compared to values obtained from vertical hydraulic gradient and hydraulic conductivity measurements. The fluxes estimated by the heat tracing methods exhibit a trend that partly follows the conceptual model of a pool-riffle-pool sequence. The directly calculated fluxes mostly agree with heat tracing based estimates. The deviation in flux distribution from the conceptual “downwelling-upwelling” model is partly due to the dominantly loosing conditions at the study site. Moreover, varying assumptions concerning boundary conditions and physical properties of the streambed that are intrinsic to the analytical models produce somewhat inconsistent results between methods. Careful selection of a model for heat tracing is vital to obtaining accurate fluid flux estimates. Click on the image of the poster to download a PDF of the poster.

[1] Bredehoeft, J. D., and I. S. Papaopulos. 1965. Rates of vertical groundwater
movement estimated from the Earth’s thermal profile. Water Resources Research
1: 325-328. (PDF link)
[2] Hatch, C. E., A. T. Fisher, J. S. Revenaugh, J. Constantz, and C. Ruehl. 2006.
Quantifying surface water-groundwater interactions using time series analysis
of streambed thermal records: Method development. Water Resources Research 42. (PDF link)
[3] Keery, J., A. Binley, N. Crook, and J. W. N. Smith. 2007. Temporal and spatial variability
of groundwater-surface water fluxes: Development and application of an analytical
method using temperature time series. Journal of Hydrology 336: 1-554 16. (PDF link)
[4] Schmidt, C., B. Conant, M. Bayer-Raich, and M. Schirmer. 2007. Evaluation and
field-scale application of an analytical method to quantify groundwater discharge
using mapped streambed temperatures. Journal of Hydrology 347: 292-307. (PDF link)