Evaluation of a model framework to estimate soil and soil organic carbon redistribution by water and tillage using 137Cs in two U.S. midwest agricultural fields

Authors: YOUNG, C - Collaborator; LIU, SHUGUANG - Collaborator; SCHUMACHER, J - South Dakota State University; SCHUMACHER, T - South Dakota State University; Kaspar, Thomas; McCarty, Gregory; NAPTON, D - South Dakota State University; Jaynes, Dan

Submitted to: Geoderma
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/24/2014
Publication Date: 6/14/2014
Citation: Young, C.J., Liu, S., Schumacher, J.A., Schumacher, T.E., Kaspar, T.C., Mccarty, G.W., Napton, D., Jaynes, D.B. 2014. Evaluation of a model framework to estimate soil and soil organic carbon redistribution by water and tillage using 137Cs in two U.S. midwest agricultural fields. Geoderma. 232-234:437-448. https://doi.org/10.1016/j.geoderma.2014.05.019.
DOI: https://doi.org/10.1016/j.geoderma.2014.05.019

Interpretive Summary: Projected global warming and degradation of land resources by erosion are among the most pressing environmental challenges facinc agriculture. Soil organic carbon (SOC) plays a considerable and unique role in the global carbon cycle. Within agricultural lands, soil erosion may be a dominant force in redistribution of SOC within landscapes and this redistribution may impact C oxidation or storage. The main objective of this study is to evaluate a soil modeling framework and to estimate and understand the soil and SOC redistribution caused by water and tillage erosion in two agricultural fields in Iowa of the U.S. Midwest having corn-soybean rotation and different tillage practices. The modeling effort optimized parameters for rill and sheet erosion within the model. The results indicated that carbon in eroded soil is deposited in lower landscape positions and also indicated the importance of soil redistribution processes on SOC dynamics in agricultural landscapes. This model framework can help to improve the information about the spatial distribution of soil erosion across agricultural landscapes and to gain a better understanding of SOC dynamics within eroded fields.

Technical Abstract: Cultivated lands in the U.S. Midwest have been affected by soil erosion causing environmental and agricultural problems, including the redistribution of soil organic carbon (SOC) in the landscape. However, the importance of SOC redistribution effect in soil productivity and crop yield is still uncertain. In this study, we used a model framework, which includes the Unit Stream Power based - Erosion Deposition (USPED) and the Tillage Erosion Prediction (TEP) models, to understand the soil and SOC redistribution caused by water and tillage erosion in two agricultural areas in the U.S. Midwest. This model framework was calibrated and validated for different digital elevation model (DEM) spatial resolutions (10 m, 24 m, 30 m, and 56 m) and topographic exponents m (1.0-1.6) and n (1.0-1.3) for water erosion using soil redistribution rates determined from 137Cs measurements. The results showed that the aggregated 24 m DEM, m = 1.4 and n = 1.0 for rill erosion, and m = 1.0 and n = 1.0 for sheet erosion provided the best fit with the observation data in both sites. Moreover, estimated SOC redistribution in the two field sites were 1.3 ± 9.8 g C m-2 y-1 in the field site 1 and 3.6 ± 14.3 g C m-2 yr-1 in the field site 2, which suggests that part of the carbon in eroded soil is deposited in lower landscape positions. This study demonstrated the importance and dependency of modeling soil redistribution with the spatial resolution and the topographic exponents, and the effect of soil redistribution on the SOC dynamics through the landscape. Furthermore, this approach can be used to assess soil and SOC redistribution in agricultural landscapes. Additional research is needed to improve the application of the model framework for use in regional studies where variability of rainfall erosivity and cover management factors are also important. Therefore, using this model framework can help to improve the information about the spatial distribution of soil erosion across agricultural landscapes and to gain a better understanding of SOC dynamics within eroding and formerly eroded fields.