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

Abstract

Cultivated lands in the U.S. Midwest have been affected by soil erosion, causing soil organic carbon (SOC) redistribution in the landscape and other environmental and agricultural problems. The importance of SOC redistribution on soil productivity and crop yield, however, 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 evaluated 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) using soil redistribution rates 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 at both sites. Moreover, estimated average SOC redistributions were 1.3±9.8g Cm−2yr−1 in field site 1 and 3.6±14.3g Cm−2yr−1 in field site 2. Spatial distribution patterns showed SOC loss (negative values) in the eroded areas and SOC gain (positive value) in the deposition areas. This study demonstrated the importance of the spatial resolution and the topographic exponents to estimate and map soil redistribution and the SOC dynamics throughout the landscape, helping to identify places where erosion and deposition from water and tillage are occurring at high rates. Additional research is needed to improve the application of the model framework for use in local and regional studies where rainfall erosivity and cover management factors vary. 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 previously eroded fields.