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Author ORCID Identifier

https://orcid.org/0000-0002-4408-9321

AccessType

Open Access Dissertation

Document Type

dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Geosciences

Year Degree Awarded

2021

Month Degree Awarded

September

First Advisor

Isaac Larsen

Subject Categories

Geomorphology | Natural Resources and Conservation | Soil Science

Abstract

Fertile, agricultural productive soils are essential for producing food for a growing global population. Soil erosion diminishes soil quality, threatens food security by decreasing crop productivity, and degrades ecosystem health through increased rates of sedimentation and runoff. Despite decades and thousands of soil erosion studies, robust scalable methods for estimating the magnitude and rates of soil erosion have been elusive. In this dissertation, we develop a remote sensing method for quantifying the areal extent of historical loss in an agricultural landscape and provide a method for estimating the total thickness of soil loss and rates of historical soil loss in agricultural systems. First, we develop a remote sensing index for estimating soil organic carbon concentrations, which is the primary chemical difference between fertile A-horizon and less fertile B-horizon soils. Because the index only relies on the visible spectrum, it can be used to map soil organic carbon variability at the field scale. We test the index in a field in Iowa and find that the index predicts organic carbon concentrations with a root mean square error of 0.54%. Soil moisture can confound the spectral signature of soil organic carbon, but we quantify the effect of soil moisture on the remote sensing index by measuring changes in the index for wet and dry soils with a range of soil organic carbon concentrations. Moisture has the largest influence on soils with higher soil organic carbon concentrations than soils with lower organic carbon concentrations. We also performed a laboratory experiment to quantify the time for the surface layer of a soil to dry and find that the surface dries after ~27 hours, indicating that moisture has little influence on the spectral signal of the surface soil around one day following precipitation. We use the soil organic carbon index calculated from high-resolution satellite imagery to map soil organic carbon in agricultural fields at 28 locations throughout the midwestern U.S. We then used high-resolution satellite and LiDAR data to develop a relationship between A-horizon loss and topographic curvature, and then use topographic data to scale-up soil loss predictions across 3.9x105 km2 of midwestern U.S. Our results indicate that 35±11% of the cultivated area has lost A-horizon soil, and that prior estimates of soil degradation from soil survey-based methods have significantly underestimated A-horizon soil loss.

Finally, we quantify the historically averaged soil erosion rate and the total depth of soil loss throughout the Midwestern U.S. In the Midwestern U.S., erosion has caused native prairie remnants to become perched above surrounding farmland, providing an opportunity to measure historical soil loss. We used high-resolution topographic surveys conducted across erosional escarpments at the boundary between 20 prairies and adjacent fields and show the median depth of soil loss ranges from 0.04-0.69 m, corresponding to erosion rates of 0.2–4.3 mm yr-1.

DOI

https://doi.org/10.7275/23565835

Available for download on Thursday, September 01, 2022

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