Carbon sequestration in agricultural soils is critical to mitigating climate change, but the carbon credit market is limited by the high cost of ground-truth data collection for monitoring, reporting, and verification (MRV). This project develops UAS-based cyber-physical systems to dramatically lower the cost of MRV for soil carbon and water content.
Approach: Dig, Sip, Breathe
The project name reflects three complementary sensing modalities:
- Dig: UAS equipped with augering mechanisms extract soil core samples and insert time-domain reflectometry (TDR) sensors to measure soil water content (SWC) and soil organic carbon (SOC)
- Sip: UAS collect water samples to characterize runoff and water quality indicators
- Breathe: Mobile, power-tethered UAS with sensors along the tether persistently monitor atmospheric columns -- measuring temperature, CO2, wind, and other atmospheric traits over agricultural fields
Research Goals
- Persistent atmospheric column sensing using automated tethered UAS with sensors that can be dynamically positioned along the tether for high-resolution, long-duration measurements
- Novel sampling modalities and intelligent prediction through UAS that physically interact with soil to extract samples and insert sensors, combined with machine learning to predict soil properties
- Smart agricultural sampling through automated task planning that uses real-time feedback from tethered monitoring and sampling UAS to target key locations, saving time, energy, and improving verification accuracy
Impact
By automating and improving MRV practices, this work has the potential to fundamentally change farm and ranch economics around carbon credits, putting better tools in the hands of farmers and ranchers while advancing the science of agricultural carbon monitoring.