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Increasing traffic intensities in agricultural work processes increase the risk of subsoil compaction. The objective of this study is to investigate whether the geometry of the field and size of the machine influence the traffic intensity. This study focuses on analysing the influence of the machinery and field geometry on the traffic intensities in the field based on wheat harvest operations performed with one combined harvester. For this purpose, 177 routes on 59 different fields are simulated with a route planner, and subsequently, the tracks and traffic intensities are modelled. The structure of the field was specified using eight different shape indices. The analyses showed that the configuration of the machines mainly influences the total passed area and the wheel load distribution on the field. Independent of the machine, the geometry of the field has an influence on the area proportions in the headland with wheel passes above 5 and 10. The indices that highly correlate with traffic intensity are the mean interior edge ratio, the interior area ratio and the mean fractal dimension. It means that the larger the field area in proportion to the perimeter and the infield area, the larger the area fraction with more than 5 or 10 passes. Moreover, this area share increases with the complexity of the field geometry, expressed by the mean fractal dimension. Consequently, the size of the field mainly influences the traffic in the headland because of the removal of the crop. [ABSTRACT FROM AUTHOR]

Soil compaction by field traffic is one of the main threats to all agricultural soils worldwide. For instance, compacted soils have a reduced hydraulic conductivity, which leads to an increased surface runoff and thus to an increased flood risk. To mitigate further soil degradation by field traffic, it is important to know where, when and to what extent soil compaction may occur. This study demonstrates a new approach to model the soil compaction risk at regional scale. The developed model is called "SaSCiA" (Spatially explicit Soil Compaction risk Assessment). SaSCiA generates daily maps of soil compaction risk by integrating (i) spatial soil and crop type information, (ii) crop type depended machinery information, (iii) daily weather information, (iv) an agro-ecosystem model (MONICA) to compute daily soil moisture information and (v) different approaches to calculate the soil strength and soil stress. By integrating soil moisture calculations and the present crop type which is derived from satellite data (Landsat 8, Sentinel-2A), SaSCiA enables a spatially and temporal highly resolved analyses of soil degradation by soil compaction exceeding all available approaches. To demonstrate the applicability of the model, SaSCiA was applied to two regions in northern Germany. The results show that soil compaction risk varies strongly in space and time throughout the year. Applying the SaSCiA-model enables a detailed spatio-temporal analysis of the soil compaction risk and thus the identification of areas, which are exposed to soil degradation by soil compaction. Furthermore, SaSCiA may support farmers, stakeholders and consultants in their decision-making for a more sustainable soil management. [ABSTRACT FROM AUTHOR]

Soil compaction is a widespread phenomenon in today's intensive agriculture. Fields are frequented by agricultural machinery several times a year. Wheel load, contact area and the number of rollovers are important factors that determine the intensity and effect of agricultural machinery on the soil and its functionality. Unfortunately, knowledge about spatial distribution of wheel load or number of wheel passages is limited. Thus, an assessment of field traffic effects on soil functionality at spatial scales is impeded. Therefore, a model (called FiTraM; Field Traffic Model) has been developed that enables the reconstruction of the tracks and intensities of agricultural machinery at field scale using GPS tracks. To demonstrate its usability, FiTraM was applied at a study area in Lower Saxony to model the field traffic intensity for a 3-year crop-rotation.As a result, the headlands are crossed 50 times a year in some areas of the field- about 95 % of all areas with a wheel load over 5 tonnes. The crop zone of the field is crossed 30 times a year at certain points - the proportion of area driven with a wheel load over 5 tonnes is lower than in the headlands.The results provide initial indications of field traffic intensity at field scale and its impact on the soil. [ABSTRACT FROM AUTHOR]