Quantifying effects of root systems of planted and natural vegetation on rill detachment and erodibility of a loessial soil

Authors: LIU, JUN'E - Shaanxi Normal University; Zhang, Xunchang; ZHOU, ZHENGCHAO - Shaanxi Normal University

Submitted to: Soil & Tillage Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/10/2019
Publication Date: 10/3/2019
Citation: Liu, J., Zhang, X.J., Zhou, Z. 2019. Quantifying effects of root systems of planted and natural vegetation on rill detachment and erodibility of a loessial soil. Soil & Tillage Research. 195:104420. https://doi.org/10.1016/j.still.2019.104420.
DOI: https://doi.org/10.1016/j.still.2019.104420

Interpretive Summary: Root is a key factor reducing rill detachment and erodibility, and its effectiveness are influenced by root densities and vegetation types. Different root density parameters have been conveniently used in the literature without in-depth comparison. Moreover, few studies were conducted to quantify the differences in effectiveness of root systems on rill erodibility between planted and natural vegetation. The objectives of this study were to investigate the best root parameter to describe rill detachment, and to compare the effectiveness of planted and natural vegetation on soil physical properties and in reducing rill detachment and erodibility. Laboratory-concentrated flow flume tests were performed with undisturbed soil samples from lab with planted ryegrass and natural vegetation under 12 to 36-a restoration. The results showed that root systems of restored natural vegetation ameliorated soil properties more profoundly than those of lab due to stronger bonding and binding effects, resulting in a lower absolute soil detachment rate for a given root density. Relative soil detachment ratio was used to isolate the effects of roots on rill detachment and erodibility, and root length density was found the best predictor for estimating such effects for both planted ryegrass and natural vegetation, with exponential decay equations. The decay exponents were more negative for natural vegetation than for planted species because of the existence of more complex root networks under more diverse natural vegetation. The vegetation types should be considered in adjusting these equations for more accurate estimation of rill erodibility in process-based soil erosion models. This work would be useful to soil erosion modelers to develop more accurate erosion prediction tools to better simulate vegetation effects on soil erosion.

Technical Abstract: Root is a key factor reducing rill detachment and erodibility, and its effectiveness are influenced by root densities and vegetation types. Different root density parameters have been conveniently used in the literature without in-depth comparison. Moreover, few studies were conducted to quantify the differences in effectiveness of root systems on rill erodibility between planted and natural vegetation. The objectives of this study were to investigate the best root parameter to describe rill detachment, and to compare the effectiveness of planted and natural vegetation on soil physical properties and in reducing rill detachment and erodibility. Laboratory-concentrated flow flume tests were performed with undisturbed soil samples from lab with planted ryegrass and natural vegetation under 12 to 36-a restoration. The results showed that root systems of restored natural vegetation ameliorated soil properties more profoundly than those of lab due to stronger bonding and binding effects, resulting in a lower absolute soil detachment rate for a given root density. Relative soil detachment ratio was used to isolate the effects of roots on rill detachment and erodibility, and root length density was found the best predictor for estimating such effects for both planted ryegrass and natural vegetation, with exponential decay equations. The decay exponents were more negative for natural vegetation than for planted species because of the existence of more complex root networks under more diverse natural vegetation. The vegetation types should be considered in adjusting these equations for more accurate estimation of rill erodibility in process-based soil erosion models.