Evaluation of surface roughness parameters in agricultural soils with different tillage conditions using a laser profile meter
•21 roughness parameters were selected and evaluated on different agricultural tilled soils.•Parameters LD and MUD were the most suitable for differentiating and characterizing different tillage types.•Parameters LS and crossover lengths (lSMV and lRMS) were the most sensitive to the effect of preci...
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| Published in | Soil & tillage research Vol. 161; pp. 19 - 30 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.08.2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0167-1987 1879-3444 1879-3444 |
| DOI | 10.1016/j.still.2016.02.013 |
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| Abstract | •21 roughness parameters were selected and evaluated on different agricultural tilled soils.•Parameters LD and MUD were the most suitable for differentiating and characterizing different tillage types.•Parameters LS and crossover lengths (lSMV and lRMS) were the most sensitive to the effect of precipitation.•Many parameters were strongly correlated and thus provided very similar information.
Surface roughness crucially affects the hydrological and erosive behaviours of soils. In agricultural areas surface roughness is directly related to tillage, whose action strongly affects the key physical properties of soils and determines the occurrence and fate of several processes (e.g., surface storage, infiltration, etc.). The characterisation of surface roughness as a result of tillage operations is not straightforward, and numerous parameters and indices have been proposed for quantifying it. In this article, a database of 164 profiles (each 5m long), measured in 5 different roughness classes, was analysed. Four roughness classes corresponded to typical tillage operations (i.e., mouldboard, harrow, seedbed, etc.), and the fifth represented a seedbed soil that was subject to rainfall. The aim of the research was to evaluate and select the surface roughness parameters that best characterised and quantified the surface roughness caused by typical tillage operations. In total, 21 roughness parameters (divided into 4 categories) were assessed. The parameters that best separated and characterised the different roughness classes were the limiting elevation difference (LD) and the Mean Upslope Depression index (MUD); however, the parameters most sensitive to rainfall action on seedbed soils were limiting slope (LS) and the crossover lengths measured with the semivariogram method (lSMV) and the root mean square method (lRMS). Many parameters had high degrees of correlation with each other, and therefore gave almost identical information. The results of this study may contribute to the understanding of the surface roughness phenomenon and its parameterisation in agricultural soils. |
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| AbstractList | Surface roughness crucially affects the hydrological and erosive behaviours of soils. In agricultural areas surface roughness is directly related to tillage, whose action strongly affects the key physical properties of soils and determines the occurrence and fate of several processes (e.g., surface storage, infiltration, etc.). The characterisation of surface roughness as a result of tillage operations is not straightforward, and numerous parameters and indices have been proposed for quantifying it. In this article, a database of 164 profiles (each 5m long), measured in 5 different roughness classes, was analysed. Four roughness classes corresponded to typical tillage operations (i.e., mouldboard, harrow, seedbed, etc.), and the fifth represented a seedbed soil that was subject to rainfall. The aim of the research was to evaluate and select the surface roughness parameters that best characterised and quantified the surface roughness caused by typical tillage operations. In total, 21 roughness parameters (divided into 4 categories) were assessed. The parameters that best separated and characterised the different roughness classes were the limiting elevation difference (LD) and the Mean Upslope Depression index (MUD); however, the parameters most sensitive to rainfall action on seedbed soils were limiting slope (LS) and the crossover lengths measured with the semivariogram method (lSMV) and the root mean square method (lRMS). Many parameters had high degrees of correlation with each other, and therefore gave almost identical information. The results of this study may contribute to the understanding of the surface roughness phenomenon and its parameterisation in agricultural soils. •21 roughness parameters were selected and evaluated on different agricultural tilled soils.•Parameters LD and MUD were the most suitable for differentiating and characterizing different tillage types.•Parameters LS and crossover lengths (lSMV and lRMS) were the most sensitive to the effect of precipitation.•Many parameters were strongly correlated and thus provided very similar information. Surface roughness crucially affects the hydrological and erosive behaviours of soils. In agricultural areas surface roughness is directly related to tillage, whose action strongly affects the key physical properties of soils and determines the occurrence and fate of several processes (e.g., surface storage, infiltration, etc.). The characterisation of surface roughness as a result of tillage operations is not straightforward, and numerous parameters and indices have been proposed for quantifying it. In this article, a database of 164 profiles (each 5m long), measured in 5 different roughness classes, was analysed. Four roughness classes corresponded to typical tillage operations (i.e., mouldboard, harrow, seedbed, etc.), and the fifth represented a seedbed soil that was subject to rainfall. The aim of the research was to evaluate and select the surface roughness parameters that best characterised and quantified the surface roughness caused by typical tillage operations. In total, 21 roughness parameters (divided into 4 categories) were assessed. The parameters that best separated and characterised the different roughness classes were the limiting elevation difference (LD) and the Mean Upslope Depression index (MUD); however, the parameters most sensitive to rainfall action on seedbed soils were limiting slope (LS) and the crossover lengths measured with the semivariogram method (lSMV) and the root mean square method (lRMS). Many parameters had high degrees of correlation with each other, and therefore gave almost identical information. The results of this study may contribute to the understanding of the surface roughness phenomenon and its parameterisation in agricultural soils. |
| Author | Martinez-Agirre, Alex Giménez, Rafael Álvarez-Mozos, Jesús |
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| Snippet | •21 roughness parameters were selected and evaluated on different agricultural tilled soils.•Parameters LD and MUD were the most suitable for differentiating... Surface roughness crucially affects the hydrological and erosive behaviours of soils. In agricultural areas surface roughness is directly related to tillage,... |
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| SourceType | Open Access Repository Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 19 |
| SubjectTerms | agricultural land Agricultural soils harrows Ontario rain roughness Roughness parameters seedbeds Surface roughness surface storage Tillage |
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| Title | Evaluation of surface roughness parameters in agricultural soils with different tillage conditions using a laser profile meter |
| URI | https://dx.doi.org/10.1016/j.still.2016.02.013 https://www.proquest.com/docview/1836634693 https://hdl.handle.net/2454/22675 |
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