How Surface Conditions Affect Sediment and Chemical Transport

Abstract: Soil erosion process research produces knowledge and science used in the development of current process-based erosion prediction models. This paper highlights recent progresses at the USDA-ARS National Soil Erosion Research Laboratory (NSERL) on effects of soil surface conditions, i.e., roughness and moisture gradient, on sediment and chemical transport. We showed that surface depression caused a delay in runoff initiation. But once runoff was initiated, surfaces with depressions did not show any sediment reduction as compared those without depressions. On the surface hydrologic effects, saturation and seepage conditions greatly enhanced sediment and chemical transport. These findings showed the importance of understanding surface condition effects for better management strategies to minimize the sediment and chemical transport at the landscape. Also included in this paper are brief descriptions on experimental techniques using (1) a line-scan laser system to measure surface microtopography; and (2) a multiple-box system to quantify processes at a hillslope segment

Improved USLE-K factor prediction: A case study on water erosion areas in China

Soil erodibility (K-factor) is an essential factor in soil erosion prediction and conservation practises. The major obstacles to any accurate, large-scale soil erodibility estimation are the lack of necessary data on soil characteristics and the misuse of variable K-factor calculators. In this study, we assessed the performance of available erodibility estimators Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation (RUSLE), Erosion Productivity Impact Calculator (EPIC) and the Geometric Mean Diameter based (Dg) model for different geographic regions based on the Chinese soil erodibility database (CSED). Results showed that previous estimators overestimated almost all K-values. Furthermore, only the USLE and Dg approaches could be directly and reliably applicable to black and loess soil regions. Based on the nonlinear best fitting techniques, we improved soil erodibility prediction by combining Dg and soil organic matter (SOM). The NSE, R2 and RE values were 0.94, 0.67 and 9.5% after calibrating the results independently; similar model performance was showed for the validation process. The results obtained via the proposed approach were more accurate that the former K-value predictions. Moreover, those improvements allowed us to effectively establish a regional soil erodibility map (1:250,000 scale) of water erosion areas in China. The mean K-value of Chinese water erosion regions was 0.0321 (t ha h)·(ha MJ mm)−1 with a standard deviation of 0.0107 (t ha h)·(ha MJ mm)−1; K-values present a decreasing trend from North to South in water erosion areas in China. The yield soil erodibility dataset also satisfactorily corresponded to former K-values from different scales (local, regional, and national)

The effects of raindrop impact and runoff detachment on hillslope soil erosion and soil aggregate loss in the Mollisol region of Northeast China

Soil aggregates profoundly influence soil fertility and soil erosion. A large number of studies have showed that soil aggregate loss was mainly affected by raindrop impact and runoff detachment during hillslope erosion process; however, few attempts have been made to investigate which one plays the dominant role in soil aggregate loss. Therefore, a laboratory study was conducted to quantify the effects of raindrop impact and runoff detachment on soil erosion and soil aggregate loss during hillslope erosion processes. A soil pan (8 m long, 1.5 m wide, and 0.6 m deep and with an adjustable slope gradient of 0&ndash;35 ) was subjected to rainfall simulation experiments under two soil surface conditions: with and without raindrop impact through placing nylon net over soil pan. Two rainfall intensities (50 and 100 mm h 1) of representative erosive rainfall and two slope gradients (5 and 10 ) in the Mollisol region of Northeast China were subjected to two soil surface conditions. The results showed that raindrop impact played the dominant role in hillslope soil erosion and soil aggregate loss. Soil loss caused by raindrop impact was 3.6&ndash;19.8 times higher than that caused by runoff detachment. The contributions of raindrop impact to hillslope soil erosion were 78.3% to 95.2%. As rainfall intensity and slope gradient increased, soil loss caused by raindrop impact and runoff detachment both increased. The loss of each size aggregate was greatly reduced by 46.6&ndash;99.4% after eliminating raindrop impact. Meanwhile, the contributions of raindrop impact to the &gt;2, 1&ndash;2, 0.5&ndash;1, 0.25&ndash;0.5 and &lt;0.25 mm soil aggregate loss were 79.1% to 89.7%. Eliminating raindrop impact reduced rainfall intensity effect and increased slope gradient impact on aggregate loss.</div