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ARS Home » Midwest Area » Ames, Iowa » National Laboratory for Agriculture and The Environment » Agroecosystems Management Research » Research » Publications at this Location » Publication #297971
Title: 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

Author
item YOUNG, CLAUDIA - Us Geological Survey (USGS)
item LIU, SHUGUANG - Us Geological Survey (USGS)
item SCHUMACHER, JOSEPH - South Dakota State University
item SCHUMACHER, THOMAS - South Dakota State University
item Kaspar, Thomas
item McCarty, Gregory
item NAPTON, DARRELL - South Dakota State University
item Jaynes, Dan

Submitted to: Geoderma
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/25/2014
Publication Date: 6/15/2014
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. 232:437-448. Available at: http://www.sciencedirect.com/science/journal/00167061/232.

Interpretive Summary: Cultivated lands in the U.S. Midwest have been affected by soil erosion causing environmental and agricultural problems, including loss of productivity and the redistribution soil organic carbon (SOC) in fields. The importance of SOC redistribution on soil productivity and carbon dioxide emissions is still uncertain. In this study, we used a model framework, which includes the Unit Stream Power based - Erosion Deposition and the Tillage Erosion Prediction models, to understand the soil and SOC redistribution caused by water and tillage erosion in two agricultural fields in the U.S. Midwest. This model framework was calibrated and validated for different digital elevation model spatial resolutions and topographic exponents for water erosion using soil redistribution rates determined from radioisotope measurements (Cesion 137). The results showed that the model framework for combining the two erosion models could adequately predict soil redistribution this agricultural landscape. Soil organic carbon redistribution was then calculated from the soil redistribution estimates, soil carbon measurements, and an enrichment factor. This showed that part of the carbon from soil eroded from higher landscape positions in eroded soil is deposited in lower landscape positions. This study showed that the model framework can be coupled with geographic information systems LIDAR elevation data to assess soil and SOC redistribution in agricultural landscapes on large scales. Additional research is needed to improve the application of the model framework for use in regional studies where rainfall erosivity and cover management factors vary across the region. This modeling approach will be useful to modelers, scientists, NRCS personnel, and policy makers when evaluating the effect of agricultural practices on soil and water quality in large watersheds or on a regional scale.

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 on 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 fields 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 field site 1 and 3.6 ± 14.3 g C m-2 yr-1 in field site 2, which suggests that part of the carbon in eroded soil is deposited in lower landscape positions. This study demonstrated the importance of the spatial resolution and the topographic exponents for modeling soil redistribution, and the effect of soil redistribution on the SOC dynamics throughout 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 rainfall erosivity and cover management factors vary across the region. Therefore, using this model framework can help to improve predictions of the spatial distribution of soil erosion across agricultural landscapes and to gain a better understanding of SOC dynamics within eroding and formerly eroded fields.