Integrating Sensors, Remote Sensing and DNDC Model for Quantifying GHG Emissions

Spatial and temporal variability of soil carbon stocks and soil environmental drivers that cause the production and flux of nitrous oxide (N2O) across agricultural systems create challenges for cost effective quantification of N2O emissions and soil carbon stock changes at scale. Technological innovations sensor technologies, remote sensing technologies, cost effective metagenomics sequencing and improved mechanistic understanding of microbial and physical processes that drive soil carbon and nitrogen cycling and greenhouse (GHG) emissions provides a transformational opportunity to cost effectively quantify soil carbon and N2O emissions at sub-field scales. Dagan proposes to build, validate and demonstrate an integrated system for reliable and cost-effective measurement of field level soil carbon and N2O emissions, thereby directly addressing the SMARTFARM program objective. This system will consist of the following four components: field sampling and measurement system; subfield scale process modeling for quantifying soil carbon and GHG emissions; detailed model validation system for quantification of model uncertainty; and operational platform for implementing the system at scale. The system is designed to provide an alternative quantification platform for N2O and soil carbon estimates compared to direct measurement on all fields to provide a lower costs point for supporting quantification of carbon intensity of feedstock production with rigorous quantification of uncertainty in support of Low Carbon Fuel Standard (LCFS). System will enable feedstock producers to make informed and economic decisions to reduce carbon intensity of their feedstock production systems to enhance the economic and energy security of US bioenergy program.