GSA Annual Meeting in Denver, Colorado, USA - 2016

Paper No. 339-17
Presentation Time: 9:00 AM-6:30 PM

MEASUREMENT OF AEOLIAN PROCESSES WITH A ROBOTIC PLATFORM


QIAN, Feifei1, LANCASTER, Nicholas2, NIKOLICH, George3, JEROLMACK, Douglas J.4, ROBERTS, Sonia1, REVERDY, Paul1, VAN PELT, R. Scott5, ZOBECK, Ted M.5, SHIPLEY, Thomas6, ADHIKARI, Pramod2 and KODITSCHEK, Daniel1, (1)Department of Electrical and Systems Engineering, University of Pennsylvania, 200 S 33rd St, Philadelphia, PA 19104, (2)Desert Research Institute, Division of Earth & Ecosystem Sciences, 2215 Raggio Parkway, Reno, NV 89512-1095, (3)Division of Atmospheric Sciences, Desert Research Institute, 755 E. Flamingo Road, Las Vegas, NV 89119, (4)University of Pennsylvania, Philadelphia, PA 19104, (5)Wind Erosion and Water Conservation Research Unit, USDA-ARS, 302 W. I-20, Big Spring, TX 79720, (6)Department of Psychology, Temple University, 1701 North 13th Street, 6th Floor Weiss Hall, Philadelphia, PA 19122, fqian@seas.upenn.edu

Understanding the dynamics of sand movement on dunes and dust emissions from natural and disturbed surfaces requires measurements of boundary layer winds and rates of sediment transport and dust emissions at high temporal and spatial resolution during strong wind events.

Existing instrumentation has many limitations: installing it is very labor intensive and disturbs the fragile surfaces of interest. Once installed, it is fixed in space, and can only be deployed for a short time. The very existence of the instruments affects the wind field and probably the rates of sediment transport.

Legged robots are agile and have proved to be able to cope with the challenges of a mobile substrate and a harsh environment, and can carry a versatile instrument package to measure wind speed and direction, sand transport, and dust emissions, located in space and time using a high-resolution GPS receiver. We now have a new technology to address a central problem in aeolian research – how to get good measurements of critical parameters in difficult conditions.

We present the results of our initial field experiments at White Sands National Monument and Jornada Experimental Range that demonstrate that our robotic platform can collect meaningful data sets on surface conditions, near-surface winds, sand transport rates, and dust emissions during transport events.