Fields of bedforms such as ripples and dunes under air or water form some of the most striking patterns on Earth, Mars and other planets. How these patterns form is largely unknown. This research seeks to understand bedform-pattern development by testing the hypothesis that the patterns self-organize. Specifically, the research explores the interactions of the bedforms themselves within a set of environmental boundary conditions as the prinicpal control on the form and evolution of the patterns. The boundary conditions, which are different for every field of bedforms, control the frequency and style of interactions to yield patterns that are broadly similar, but are unique in their detail from field to field. This research will create time-series of high-resolution, three-dimensional digital maps that allow for unprecedented documentation of bedform topography, interactions among the bedforms, and pattern evolution across a representative suite of environments that differ significantly in their boundary conditions. This project uses (1) air-borne LiDAR to explore the aeolian dune field at White Sands, New Mexico, (2) low-altitude aerial photography to characterize the shallow North Loup River, Nebraska, and (3) multibeam acoustic surveys to resolve the deep Mississippi River, southern Louisiana. In addition, experimentation within the North Loup River will include using a field flume to explore the control of channel width upon pattern formation. Results of this study will provide the quantitative data necessary to fully understand the unsteady, self-organizing behavior of dunes and dune fields that arise as a consequence of the feedbacks between fluid flow, sediment erosion/deposition, and surface topography.
The transport of sand in dunes and rivers can modify the landscape at both large and small scales. Data collected for this project will improve the knowledge of how topography changes in time and space as a result of sand movement; these are the proceses that primarily control the evolution of landforms on Earth and other planets. Methodologies and techniques developed for this research project will advance the real-time monitoring of Earth's surface that is necessary to document progressive environmental change, information that is vital for the successful management of natural resources.
