FiTraM: A model for automated spatial analyses of wheel load, soil stress and wheel pass frequency at field scale

Augustin, Katja; Kuhwald, Michael; Brunotte, Joachim; Duttmann, Rainer

doi:10.1016/j.biosystemseng.2019.01.019

Cited by 12 publications

(9 citation statements)

References 37 publications

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“…-Application of Frida (Schjønning et al, 2008;Schjønning et al, 2015a) and Schjønning and Lamandé (2018) for soil strength calculation -Tire: 1050/50R32, at a depth of 35 cm -Matric potential of -50 hPa Kuhwald et al (2018) -Mapping daily soil compaction risk at regional scale with high spatial resolution (20 m*20 m) -SaSCiA-model, incorporates Horn and Fleige (2003), DIN V 19688 (2011), Nendel et al (2011), Rücknagel et al (2012, 2015 -modelling of soil compaction risk beneath the wheel tracks of a complete maize season -Application of FiTraM and SaSCiA (Kuhwald et al, 2018;Augustin et al, 2019) Botta et al, 2009;Schjønning et al, 2012). Several studies exist that analyzed the various effects of wheeling on stress propagation and distribution inside the soil as on physical soil properties as well (e.g., Gebhardt et al, 2009;Lamandé and Schjønning, 2011;Hartmann et al, 2012;Keller et al, 2012;Berisso et al, 2013;Seehusen et al, 2019).…”

Section: Referencementioning

confidence: 99%

Spatio-Temporal High-Resolution Subsoil Compaction Risk Assessment for a 5-Years Crop Rotation at Regional Scale

Kuhwald

Duttmann

2022

Front. Environ. Sci.

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Soil compaction results whenever applied soil stress by machinery exceed the soil strength. Both, soil strength and stress, are spatially and temporally highly variable, depending on the weather situation, the current crop type, and the machinery used. Thus, soil compaction risk is very dynamic, changes from day to day and from field to field. The objective of this study was to analyze the spatio-temporal dynamics of soil compaction risk and to identify hot-spot areas of high soil compaction risk at regional scale. Therefore, we selected a study area (∼2,000 km2) with intensive arable farming in Northern Germany, having a high share of cereals, maize and sugar beets. Sentinel-2 images were used to derive the crop types for a 5-years crop rotation (2016–2020). We calculated the soil compaction risk using an updated version of the SaSCiA-model (Spatially explicit Soil Compaction risk Assessment) for each single day of the period, with a spatial resolution of 20 m. The results showed the dynamic changes of soil compaction risk within a year and throughout the entire crop rotation. The relatively dry years 2016 and 2018–2020 reduced the soil compaction risk even at high wheel loads applied to soil during maize and sugar beet harvest. Contrary, high precipitation in 2017 increased the soil compaction risk considerably. Focusing on the complete 5-year period, 2.7% of the cropland area was identified as hot-spots of soil compaction risk, where the highest soil compaction risk class (“extremely high”) occurred every year. Additionally, 39.8% of the cropland was affected by “extremely high” soil compaction at least in one of the 5 years. Although the soil compaction risk analysis does not provide information on the actual extent of the compacted area, the identification of risk areas within a period may contribute to understand the dynamics of soil compaction risk in crop rotation at regional scale and provide advice to mitigate further soil compaction in areas classified as high risk.

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Section: Referencementioning

confidence: 99%

Spatio-Temporal High-Resolution Subsoil Compaction Risk Assessment for a 5-Years Crop Rotation at Regional Scale

Kuhwald

Duttmann

2022

Front. Environ. Sci.

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“…Traffic‐induced adverse effects on agricultural soil can be evaluated by soil compaction models (SCMs), such as FiTraM, R package, and Terranimo (Augustin et al., 2019; de Lima et al., 2021; de Lima et al., 2018; Stettler et al., 2014). Soil compaction models are important tools for the establishment of strategies and recommendations for field operations on a small scale and environmental conservation on a large scale.…”

Section: Introductionmentioning

confidence: 99%

“…The slopes of the VCL and SL are known as compression index (C c ) and swelling index (C s ), respectively. The transition point between VCL and SL is commonly called precompression stress (σ p ) FiTraM, R package, and Terranimo (Augustin et al, 2019;de Lima et al, 2021;de Lima et al, 2018;Stettler et al, 2014). Soil compaction models are important tools for the establishment of strategies and recommendations for field operations on a small scale and environmental conservation on a large scale.…”

Section: Introductionmentioning

confidence: 99%

Effects of dry bulk density and water content on compressive characteristics of wet clayey paddy soil

et al. 2022

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The application of soil compaction models is limited by the lack of soil compression properties and their variations as a function of different physical parameters. This study aimed to explore the effect of dry bulk density and water content on the characteristics of the soil compression curves and compression properties for wet clayey paddy soil. In order to investigate large‐scale soil initial conditions, uniaxial compression tests were conducted on a total of 25 soil states by controlling five soil water contents and five dry bulk densities. Soil compression curves were obtained from fitting uniaxial compression test results, and the swelling index, compression index, and precompression stress were measured. The swelling index of paddy soil ranged from 0.003 to 0.138 and showed a significant positive dependence on water content and a significant negative correlation with dry bulk density. The compression index ranged from 0.115 to 0.839. A quadratic polynomial function was established between water content and compression index, whereas the compression index showed a significant negative correlation with dry bulk density. The precompression stress ranged from 33 to 127 kPa. The precompression stress showed a prominent negative dependence on water content and a significant positive correlation with dry bulk density. The pedo‐transfer functions of the swelling index, compression index, and precompression stress could be used in soil compaction models as input parameters for risk evaluation of compaction damage of wet clayey paddy soil.

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“…The soil resistance to penetration increased after only 4 passes of a heavy machine [17]. Tillage practices alter the soil's chemical, physical, and biological properties, which can alter the roots' traits, growth, and development [18]. The soil physical and chemical properties vary between the samples obtained where the tractor's wheels crossed them and those taken elsewhere [19].…”

Section: Introductionmentioning

confidence: 99%

Change of Some Soil Physical Properties in Newly Reclaimed Soils Following Poor Soil Management: A Case Study in Al-Qasasin, Egypt

Hussien

Abou-Baker

Fotoh

et al. 2022

AJSSPN

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Background: In newly reclaimed areas, some improper farming practices like using heavy machines in tillage, adding excessive quantity of fertilizers, irrigation by flooding method and intensity cultivation could affect the soil physical properties. Objective‎: Therefore, eighty soil samples were collected from the twenty-seven profiles to evaluate the change of soils' physical properties at four locations (A, B, C and D) after different improper soil managements. Methods‎: The study area is located in Al-Qasasin, Ismailia Governorate, Egypt northern tip of it extended between latitudes 30° 33' 1.147" N and 30° 28' 16.096" N, and longitudes 32° 4' 12.984" E and 32° 4' 15.696" E, with total area of 144.25 km2 (34345.1 Feddan) which falls in the semi-arid zone. Profile depth, soil texture, total porosity (TP), bulk density (BD), hydraulic conductivity (HC) and infiltration rate (IR) were determined according to the standard procedures. Results: According to the values of general mean of the studied properties in the four locations, BD takes the order: C>B>A>D. While the TP take the opposite trend of BD (D>A>B>C), on the other hand, both HC and IR follow the same order: C>A>B>D. These results attributed to that the locations B and D using surface flooding irrigation system, while A and C locations using sprinkler and drip irrigation systems, respectively. In addition to the intensive cultivation and the conventional tillage planting system are used in the B and D locations. Where the tillage tools like heavy plows, disks or chisels are used seasonally. While in A and C sites light tillage and orchards planting only are used commonly. Conclusion: These findings should be considered in future research to improve the soil management programs in these examined areas particularly the fourth location that should stop flooding technique and terns to the drip or sprinkler method.

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FiTraM: A model for automated spatial analyses of wheel load, soil stress and wheel pass frequency at field scale

Cited by 12 publications

References 37 publications

Spatio-Temporal High-Resolution Subsoil Compaction Risk Assessment for a 5-Years Crop Rotation at Regional Scale

Spatio-Temporal High-Resolution Subsoil Compaction Risk Assessment for a 5-Years Crop Rotation at Regional Scale

Effects of dry bulk density and water content on compressive characteristics of wet clayey paddy soil

Change of Some Soil Physical Properties in Newly Reclaimed Soils Following Poor Soil Management: A Case Study in Al-Qasasin, Egypt

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