Innovative particle tracking to quantify soil erosion and sediment transport processes under global change
- Dr. Ryan Stewart, School of Plant and Environmental Sciences
- Dr. Kevin McGuire, Forest Resources and Environmental Conservation
- Dr. W. Cully Hession, Biological Systems Engineering
- Dr. Nicholas Polys, Computer Science
Despite decades of prevention efforts, soil erosion remains among the most serious soil degradation and water quality problems facing society. Erosion causes excess stream sedimentation, which threatens water quality due to bound substances such as pesticides, nutrients, bacteria, and antibiotic resistant genes (ARGs). Issues with erosion are likely to accelerate under global change, for instance due to land use changes and greater precipitation intensities. However, current tools for measuring soil erosion processes are rudimentary, meaning that the kinetics and controls of eroding soil are not well understood. Similarly, relatively little is known about particle transit times from fields to surface water bodies, thus forming a key source of uncertainty for watershed management programs. In response to these critical knowledge gaps, we will develop soil-particle tracking sensors using Radio Frequency Identification Device (RFID) technology. Labeled particles will form a distributed soil erosion sensor that will open new opportunities to detect, quantify, and model soil transport processes.
Our main objectives are to:
1) develop sensors and detection units, and
2) verify their performance in plotscale experiments.
Our primary objectives are to develop and validate the micro-RFID particle tracking sensors, working with Microsensys, Inc., a leader in small-scale RFID technology, to develop micro-chips (< 0.5 mm) and corresponding readers for field use. However, this effort represents only the first critical step in a much larger endeavor to address pressing environmental issues with direct relevance to global system sciences and data analytics, specifically by developing technology that will have the potential to generate large and novel datasets that can better predict erosion processes under global change.
Example of a MicroSensys micro-RFID transponder and reader used to track bumblebee movement. Images from collaborator Dr. T’ai Roulston, University of Virginia.