Predicting Neutron Attenuation from Bulk Density and Moisture for Soil Carbon Measurement
Inelastic neutron scattering (INS) enables rapid, non-destructive in situ measurements of soil elemental composition over large soil volumes. Standard INS yields bulk elemental concentrations, but spatially resolved measurements require techniques such as Associated Particle Imaging (API), which pairs neutron detection with coincident alpha detection to reconstruct the location of the neutron interaction. One of the unique advantages of API is its capability to measure all major soil components simultaneously, allowing for the estimation of both bulk density and water content directly from the measured neutron-induced gamma-ray spectra. Accurate interpretation of bulk INS-API data depends on correcting for both gamma-ray and neutron attenuation in soil. Although gamma attenuation can be calculated from known mass attenuation coefficient data and density, neutron attenuation is more complex, depending on neutron energy, soil composition, bulk density, and hydrogen content from water and organic matter. We use Monte Carlo simulations of soils with varied compositions, bulk densities, and water contents to model neutron attenuation and develop a simple predictive model requiring only dry bulk density and volumetric water content. We validate this model experimentally using an INS-API system with controlled soil columns, finding agreement within 10 percent at 30 cm depth. This approach enables practical, field-ready correction of INS-API measurements for neutron attenuation, laying the groundwork for a self-consistent measurement framework that can address the elemental composition of soil carbon assessments.