Quantifying the Spatial Distribution of Soil Organic Carbon and Nitrogen Using Reflectance Spectroscopy

• Author / Creator

  Sorenson, Preston T

• Soil is a critical component of global biogeochemical cycles, and there is an increasing need for cost effective tools to measure soil carbon stocks and determine soil nitrogen contents. Reflectance spectroscopy can deliver large volumes of soil carbon data, with potential applications for understanding soil carbon distribution and assessing reclaimed soils. Reflectance spectra in the SWIR range were collected on a range of soil samples, including intact cores, using a SisuROCK automated hyperspectral imaging system in a laboratory setting. Samples were also analyzed for soil organic carbon and total nitrogen concentrations by dry combustion to prepare a training data set to use as inputs for predictive models. Predictive models were built using continuous wavelet processing along with Cubist and Bayesian Regularized Neural Net models. Overall, soil organic carbon was more aggregated in Chernozemic soils and in B and C horizons compared to A horizons. Nitrogen in turn showed more aggregation for all soil types and horizons compared to soil organic carbon. Additionally, crop rotations were revealed to influence both the concentration and distribution of carbon and nitrogen. Continuous forage rotations were found to have the highest soil organic carbon (SOC) and total nitrogen (TN) contents compared to an agro-ecological rotation for only the top 3 and 4 cm, respectively. These two rotations had comparable concentrations for both parameters for the rest of the topsoil, which was greater than the concentration of SOC and TN in a continuous grain rotation to depths of approximately 12 cm. Increases in both SOC and TN were associated with increased spatial aggregation at fine spatial scales. Reflectance spectroscopy data was also found to be valuable for reclaimed soil assessments using a Cubist statistical model. The root mean square error (RMSE), R2, and ratio of performance to deviation (RPD) values for SOC were 0.60%, 0.80, and 2.2, respectively. The TN model results were 0.05%, 0.81 and 2.5, and pH model results were 0.44, 0.69 and 1.8. In addition to a reflectance spectroscopy system, a simple two-band reflectance sensor was also evaluated for use assessing reclaimed soils. This two-band sensor could only be used for general qualitative comparisons amongst soil zones. Specifically, to identify areas with statistically significant differences in organic matter, cation exchange capacity and water content. This system could be used to map out zones with significant soil variation as part of reclamation monitoring, and then used to guide laboratory analytical sampling. Overall, these results indicate that reflectance-based sensing tools can be used to successfully measure soil properties and support the assessment of reclaimed soils.

• Subjects / Keywords

  • Soil Science

• Graduation date

  Fall 2019

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/r3-0nhq-7s45

• License

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