Toward a tool aimed to quantify soil compaction risks at a regional scale: Application to Wallonia (Belgium)

Abstract

The spatial analysis of the soil compaction risk has been developed at the regional level and applied to Wallonia (Belgium). The methodology is based on the estimation of the probability of exceeding the preconsolidation stress due to the application of loads on the soil. Preconsolidation stresses (Pc) are computed from the pedotransfer functions of Horn and Fleige (2003) at pF 1.8 and 2.5 and classified into 6 categories ranging from very low Pc (< 30 kPa) to extremely high Pc (> 150 kPa). The computation requires the knowledge of pedological (texture, organic content), mechanical (bulk density, cohesion, internal friction angle), and hydraulic variables (water content available, non-available water content, air capacity, saturated hydraulic conductivity). These variables are obtained from databases like HYPRES or AARDEWERK or from pedotransfer functions. The computation of Pc takes into account the spatial structure of the data: in some cases, data are abundant (e.g. texture data) and spatial variability is taken into account through geostatistical methods. In other cases, the data is sparse but uncertainty information can be extracted from the knowledge of the statistical distribution. Maps of the most probable Pc class are produced. Uncertainty is computed as the classification error probability. Implementation of these methods in Wallonia showed that Pc values higher than 120 kPa are reached either on 64 % of the territory at pF 2.5 or on 55 % at pF 1.8. A higher uncertainty was found at pF 2.5 than at pF 1.8. Uncertainty was also found higher for clay and clayed loess than for other textural classes present in Wallonia. The risk of compaction is defined as the probability that Pc is exceeded by the stress created by a load applied to the soil at a depth of 40 cm, the loads being similar to those induced by agricultural or forestry tires. It appeared that subsoil compaction risks exist mainly in loamy forest soils with small coarse fragments supporting loads similar to that existing on logging machines. In the zones where the uncertainty is low, the developed tool could be used as a basis for providing policy measures in order to promote soil-friendly farming and forest practices.

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“…Pre-compression computation was done to evaluate susceptibility index of soil compaction indirectly [44]. In this study, computation of Pc based on physical parameters of the soil matrix showed three distinct classes of compaction (low, medium and high) ( Fig.…”

“…In this regard, Table 1 showed that Pc and Ss are highly correlated with an R² of 90% in the boundaries and in the center of the field. This relationship provided means to assess response of soil to compaction using Pc as an indirect method that is pointed out by D'or and Destain [44], for both field and regional scales. The state of water content constitutes a determinant parameter to optimally manage timing for introducing machines in the field and avoiding traffic when soil is in its plastic state.…”

“…Other researchers have characterized soil structure using density or others measurable variables such as permeability [36][37][38][40][41][42][43]. D'or and Destain [44] classified Pc values into six ranges from very low (Pc < 30) to extremely high (Pc > 150) assigned to different levels of compaction. According to Håkansson and Lipiec [45], compaction of vertisols in Morocco is important soil knowledge that needs to be characterized.…”

Spatially Explicit Soil Compaction Risk Assessment of Arable Soils at Regional Scale: The SaSCiA-Model

“…The structure of the pedotransfer functions enables an application with freely available soil data and the transfer to the regional scale. Lebert [45] and D'Or and Destain [28], however, demonstrated that the pedotransfer functions provided by Horn and Fleige [15] tend to overestimate soil strength of certain texture classes (e.g., loam).…”

Environmental impacts of different crop rotations in terms of soil compaction

“…These models can be used to estimate and depict the site-related soil compaction risk (van den Akker and Hoogland, 2011;D'Or and Destain, 2014), for individual machinery passes or operations D efossez et al, 2003;Trautner and Arvidsson, 2003;Lozano et al, 2013), or for a combination of both (Duttmann et al, 2014). Compared to these models, the model used here can quantify and assess the soil compaction risk of entire crop rotations up to the farm level.…”