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Evaluation of surface roughness parameters in agricultural soils with different tillage conditions using a laser profile meter

机译:使用激光曲线测量法评价不同耕作条件的农业土壤粗糙度参数

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摘要

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 5 m 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.
机译:表面粗糙度至关重要地影响土壤的水文和腐蚀行为。在农业区域的表面粗糙度与耕作直接相关,其行为强烈影响土壤的关键物理性质,并确定几种方法的发生和命运(例如,表面储存,渗透等)。由于耕作操作的表面粗糙度的表征并不直接,并且已经提出了许多参数和指标来量化它。在本文中,分析了在5种不同粗糙度类别中测量的164个简档(每5米长)的数据库。四个粗糙度等于典型的耕作作业(即,MOUldBoard,Harrow,Seedbed等),第五个代表了降雨的苗床土壤。该研究的目的是评估和选择最能表现和量化由典型耕作操作引起的表面粗糙度的表面粗糙度参数。共计评估21种粗糙度参数(分为4个类别)。最佳分离和表征不同粗糙度类的参数是限制升高差(LD)和平均上升抑制指数(泥);然而,对苗木土壤上的降雨作用最敏感的参数限制了斜率(LS)和用半造型造影方法(LSMV)和根均方(LRMS)测量的交叉长度。许多参数彼此具有很高的相关性,因此提供了几乎相同的信息。该研究的结果可能有助于了解地表粗糙度现象及其在农业土壤中的参数化。

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