Micro-morphological analysis of the effect of sampling by the volumetric ring method on soil structure

2007 ◽  
Vol 3 (1) ◽  
pp. 1-19
Author(s):  
Luiz Pires ◽  
Miguel Cooper ◽  
Nivea Dias ◽  
Osny Bacchi ◽  
Klaus Reichardt
Keyword(s):  
Image Analysis ◽  
Bulk Density ◽  
Size Distribution ◽  
Soil Structure ◽  
Soil Bulk Density ◽  
Soil Samples ◽  
Pore Shape ◽  
Sampling Device ◽  
Structure Changes ◽  
Ring Method

This report investigates the effect of sampling by the volumetric ring method on pore size number and shape distributions. Soil porosity was analyzed using the micromorphological image analysis technique, which helped to explain soil structure changes near the border of samples collected in cylinders and provided detailed information about pore shape, number, and size distribution variations along the samples. Compaction due to sampling affects mainly large irregular and rounded pores of the soils utilized in this study. When evaluating inaccuracies in density measurements due to the compacted regions caused by the sampling device the average soil bulk density for each soil resulted in the ranges of 1.72 ± 0.05 g.cm −3 for Geric Ferralsol soil, 1.66 ± 0.03 g.cm −3 for Eutric Nitosol soil and 1.33 ± 0.05 g.cm −3 for Rhodic Ferralsol soil, respectively. When calculating the average soil bulk density over smaller regions, e.g. in the center of each sample (area of 17.14 mm 2 ) results reduced to 1.64 ± 0.05 g.cm −3 with Geric Ferralsol soil, 1.56 ± 0.03 g.cm −3 with Eutric Nitosol soil and 1.29 ± 0.10 g.cm −3 with Rhodic Ferralsol soil, respectively. These results clearly indicate the effect of sampling by the volumetric ring method. The use of image analysis was essential to explain compaction differences close to the border of the samples collected using cylinders (volumetric ring method) and provided detailed information about pore shape and size distribution variations within soil samples. The results are useful as indicators of the consequences of sampling on the quality of soil samples.

scholarly journals Machine-Learning Classification of Soil Bulk Density in Salt Marsh Environments

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4408
Author(s):  
Iman Salehi Hikouei ◽  
S. Sonny Kim ◽  
Deepak R. Mishra
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Salt Marsh ◽  
Bulk Density ◽  
Remote Sensing Data ◽  
Soil Bulk Density ◽  
Soil Samples ◽  
Marsh Soil ◽  
Landsat 7 ◽  
Salt Marsh Soil

Remotely sensed data from both in situ and satellite platforms in visible, near-infrared, and shortwave infrared (VNIR–SWIR, 400–2500 nm) regions have been widely used to characterize and model soil properties in a direct, cost-effective, and rapid manner at different scales. In this study, we assess the performance of machine-learning algorithms including random forest (RF), extreme gradient boosting machines (XGBoost), and support vector machines (SVM) to model salt marsh soil bulk density using multispectral remote-sensing data from the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) platform. To our knowledge, use of remote-sensing data for estimating salt marsh soil bulk density at the vegetation rooting zone has not been investigated before. Our study reveals that blue (band 1; 450–520 nm) and NIR (band 4; 770–900 nm) bands of Landsat-7 ETM+ ranked as the most important spectral features for bulk density prediction by XGBoost and RF, respectively. According to XGBoost, band 1 and band 4 had relative importance of around 41% and 39%, respectively. We tested two soil bulk density classes in order to differentiate salt marshes in terms of their capability to support vegetation that grows in either low (0.032 to 0.752 g/cm3) or high (0.752 g/cm3 to 1.893 g/cm3) bulk density areas. XGBoost produced a higher classification accuracy (88%) compared to RF (87%) and SVM (86%), although discrepancies in accuracy between these models were small (<2%). XGBoost correctly classified 178 out of 186 soil samples labeled as low bulk density and 37 out of 62 soil samples labeled as high bulk density. We conclude that remote-sensing-based machine-learning models can be a valuable tool for ecologists and engineers to map the soil bulk density in wetlands to select suitable sites for effective restoration and successful re-establishment practices.

scholarly journals Pore system changes of damaged Brazilian oxisols and nitosols induced by wet-dry cycles as seen in 2-D micromorphologic image analysis

2009 ◽  
Vol 81 (1) ◽  
pp. 151-161 ◽  
Author(s):  
Luiz F. Pires ◽  
Klaus Reichardt ◽  
Miguel Cooper ◽  
Fabio A.M. Cássaro ◽  
Nivea M.P. Dias ◽  
...  
Keyword(s):  
Image Analysis ◽  
Size Distribution ◽  
Soil Structure ◽  
Tropical Soils ◽  
Transport Processes ◽  
Structure Characterization ◽  
Control Treatment ◽  
Simple Method ◽  
Wetting And Drying ◽  
Essential Information

Soil pore structure characterization using 2-D image analysis constitutes a simple method to obtain essential information related to soil porosity and pore size distribution (PSD). Such information is important to infer on soil quality, which is related to soil structure and transport processes inside the soil. Most of the time soils are submitted to wetting and drying cycles (W-D), which can cause important changes in soils with damaged structures. This report uses 2-D image analysis to evaluate possible modifications induced by W-D cycles on the structure of damaged soil samples. Samples of three tropical soils (Geric Ferralsol, GF; Eutric Nitosol, EN; and Rhodic Ferralsol, RF) were submitted to three treatments: 0WD, the control treatment in which samples were not submitted to any W-D cycle; 3WD and 9WD with samples submitted to 3 and 9 consecutive W-D cycles, respectively. It was observed that W-D cycles produced significant changes in large irregular pores of the GF and RF soils, and in rounded pores of the EN soil. Nevertheless, important changes in smaller pores (35, 75, and 150 µm) were also observed for all soils. As an overall consideration, it can be said that the use of image analysis helped to explain important changes in soil pore systems (shape, number, and size distribution) as consequence of W-D cycles.

scholarly journals THE CHANGE OF PROPERTIES OF BROWN FOREST SOILS IN 10 YEARS ON THE TRACK “SKOLE − PARASHKA” (NPP “SKOLIVSKI BESKYDY”, UKRAINIAN CARPATHIANS)

2021 ◽  
pp. 105-128
Author(s):  
Oksana Lenevych ◽  
Zinoviy Pankiv
Keyword(s):  
Bulk Density ◽  
Forest Soils ◽  
Water Permeability ◽  
Soil Structure ◽  
Solid Phase ◽  
Forest Litter ◽  
Soil Bulk Density ◽  
Soil Reaction ◽  
Erosion Processes ◽  
Brown Forest Soils

Carry out monitoring of the track “Skole−Parashka” by the main five criteria of degradation of the natural environment: 1) width track (І category: to 0,5 m, “Unchanged track”; II category: to 1 m, “Little−changed track”; III category: 2−3 m “Endangered track”; IV category: to 5 m “Devastated track”; V category: over 5 m, “Strongly devastated track”); 2) presence of additional/parallel paths; 3) soil density; 4) quantitative and qualitative changes in vegetation (meadow ecosystems), presence/absence of forest litter (forest ecosystems); 5) the growth of erosion processes and the microrelief of the trail. It was found that for 10 years of exploitation by tourist track “Skole − Parashka” the width of the trail increased by 0,3–1,2 m. Reveal changes in soil over physical, water-physical, physicо-chemical and biotic properties of brown forest soils. The bulk density of soil structure on trails during 2012−2014 increased by approximately 32 % compared to the control, and after 10 years it increased − to 38 %. To reveal within the roadside an increase in soil bulk density from 1,07 to 1,17 g•cm-³ for 2019−2021 years. An increase in the density of the solid phase was recorded. The results of which are characteristic of the Hp horizon of brown forest soils. On the track porosity total to appraise “unsatisfactory”. For 10 years of recreational use of the track, the water permeability on the trails has not changed and was 0,07 and 0,06 mm•min-¹ according to the periods of the study (2012-2014 and 2019-2021). Within the roadside water permeability in 2012−2014 decreased by 60−80%, then in 2019−2021 years water permeability decreased by more than 90%. The actual water permeability of the soil during the downpour rains causes the intensification of surface runoff on the trail. On the track reveal abatement C organic. On the roadside track when lay to plane surface C organic unchanged within a years (2012−2014 and 2019−2021) and even was outstanding within a control. The increase C organic on the roadside is a result of “penetration” of the crushed fractions of forest litter into the H horizon during trampling and is not the result of biochemical processes. On the track increase of soil reaction (pH 5,0) while in the control pH 4,0. As to the biotic activity parameters, among the most significant are the catalase activity indices which are mostly determined by the density of the soil structure and water permeability. Key words: soil bulk density; water permeability; C organic; biotic activity; recreation influence; monitoring; NPP “Skolivski Beskydy”.

An approach to modelling soil structure dynamics and soil structure recovery due to earthworm bioturbation and root growth

2021 ◽  
Author(s):  
Katharina Meurer ◽  
Thomas Keller ◽  
Nicholas Jarvis
Keyword(s):  
Root Growth ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Bulk Density ◽  
Size Distribution ◽  
Soil Structure ◽  
Organic Matter Content ◽  
Matter Content ◽  
Structure Evolution ◽  
Static Properties

&lt;p&gt;The pore structure of soil is known to be dynamic at time scales ranging from seconds (e.g. compaction) to seasons (e.g. root growth, macro-faunal activity) and even decades to centuries (e.g. changes in organic matter content). Nevertheless, soil physical and hydraulic functions are generally treated as static properties in most soil-crop models. Some models account for seasonal variations in soil properties (e.g. bulk density) due to tillage loosening and post-tillage consolidation or soil sealing. However, no model can account for longer-term changes in soil structure due to biological agents and processes. The development of such a model remains a challenge due to the enormous complexity of the interactions in the soil-plant system. Here, we present a new concept for modelling soil structure evolution impacted by biological processes such as root growth and earthworm activity. In this preliminary test of the model, we compare simulations against field observations made at the Soil Structure Observatory (SSO) in Z&amp;#252;rich, Switzerland, that was designed to provide information on soil structure recovery following a severe compaction event. In this simple application, we modelled changes in the pore size distribution in a bare soil treatment resulting from soil ingestion and egestion by earthworms and the loosening of compacted soil by casting at the soil surface. Following calibration, the model was able to reproduce the observed temporal development of total porosity, soil bulk density and pore size distribution during a four-year period following severe traffic compaction. The modelling approach presented here appears promising and could help support the development of cost-efficient strategies for sustainable soil management and the restoration of degraded soils.&lt;/p&gt;

A new approach to modelling soil structure dynamics and a preliminary application to structure recovery by earthworm bioturbation after heavy compaction

2020 ◽  
Author(s):  
Katharina Meurer ◽  
Thomas Keller ◽  
Nick Jarvis
Keyword(s):  
Root Growth ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Bulk Density ◽  
Size Distribution ◽  
Soil Structure ◽  
Organic Matter Content ◽  
Matter Content ◽  
Structure Evolution ◽  
Static Properties

&lt;p&gt;The pore structure of soil is known to be dynamics at time scales ranging from seconds (e.g. compaction) to seasons (e.g. root growth, macro-faunal activity) and even decades to centuries (e.g. changes in organic matter content). Nevertheless, soil physical and hydraulic functions are generally treated as static properties in most soil-crop models. Some models account for seasonal variations in soil properties (e.g. bulk density) due to tillage loosening and post-tillage consolidation or soil sealing, but none can account for longer-term changes in soil structure due to biological agents and processes. Here, we present a new concept for modelling soil structure evolution impacted by biological processes such as root growth and earthworm activity. In this preliminary test of the model, we compare simulations against field observations made at the Soil Structure Observatory (SSO) in Z&amp;#252;rich, Switzerland, that was designed to provide information on soil structure recovery following a severe compaction event. In this simple application, we modelled changes in the pore size distribution in a bare soil treatment resulting from soil ingestion and egestion by earthworms and the loosening of compacted soil by casting at the soil surface. Following calibration, the model was able to reproduce the observed temporal development of total porosity, soil bulk density and pore size distribution during a four-year period following severe traffic compaction. The modelling approach presented here appears promising and could help support the development of cost-efficient strategies for sustainable soil management and the restoration of degraded soils.&lt;/p&gt;

Laboratory calibration of different soil moisture sensors in various soil types

2020 ◽  
Author(s):  
Urša Pečan ◽  
Damijana Kastelec ◽  
Marina Pintar
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Bulk Density ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Bulk Density ◽  
Soil Samples ◽  
Soil Types ◽  
Soil Moisture Sensors ◽  
Dry Soil

&lt;p&gt;Measurements of soil water content are particularly useful for irrigation scheduling. In optimal conditions, field data are obtained through a dense grid of soil moisture sensors. Most of the currently used sensors for soil water content measurements, measure relative permittivity, a variable which is mostly dependant on water content in the soil. Spatial variability of soil characteristics, such as soil texture and mineralogy, organic matter content, dry soil bulk density and electric conductivity can also alter measurements with dielectric sensors. So the question arises, whether there is a need for a soil specific calibration of such sensors and is it dependant on the type of sensor? This study evaluated the performance of three soil water content sensors (SM150T, Delta-T Devices Ltd, UK; TRIME-Pico 32, IMKO micromodultechnik GmbH, DE; MVZ 100, Eltratec trade, production and services d.o.o., SI) in nine different soil types in laboratory conditions. Our calibration approach was based on calibration procedure developed for undisturbed soil samples (Holzman et al., 2017). Due to possible micro location variability of soil properties, we used disturbed and homogenized soil samples, which were packed to its original dry soil bulk density. We developed soil specific calibration functions for each sensor and soil type. They ranged from linear to 5&lt;sup&gt;th&lt;/sup&gt; order polynomial. We calculated relative and actual differences in sensor derived and gravimetrically determined volumetric soil water content, to evaluate the errors of soil water content measured by sensors which were not calibrated for soil specific characteristics. We observed differences in performance of different sensor types in various soil types. Our results showed measurements conducted with SM150T sensors were within the range of manufacturer specified measuring error in three soil types for which calibration is not necessary but still advisable for improving data quality. In all other cases, soil specific calibration is required to obtain relevant soil moisture data in the field.&lt;/p&gt;

Least limiting water range and soil pore-size distribution related to soil organic carbon dynamics following zero and conventional tillage of a black soil in Northeast China

2014 ◽  
Vol 153 (2) ◽  
pp. 270-281 ◽  
Author(s):  
X. W. CHEN ◽  
X. H. SHI ◽  
A. Z. LIANG ◽  
X. P. ZHANG ◽  
S. X. JIA ◽  
...  
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Bulk Density ◽  
Size Distribution ◽  
Northeast China ◽  
Soil Bulk Density ◽  
Black Soil ◽  
Tillage Practices ◽  
Least Limiting Water Range ◽  
Soc Mineralization

SUMMARYThe present work built on a previous study of tillage trials, which found the effectiveness of least limiting water range (LLWR) as an indicator of soil organic carbon (SOC) mineralization under different tillage practices in a black soil of Northeast China in 2009. To improve the understanding of soil structure controls over SOC dynamics, a study was conducted to explore the relationship between LLWR, which was calculated based on soil bulk density and soil pore-size distribution, and the effects of LLWR, which was calculated based on soil bulk density and soil pore-size distribution on SOC mineralization following no tillage (NT) and mouldboard ploughing (MP). In contrast to MP, NT had a significantly greater volume of large macropores (>100 μm) at depths of 0–0·05 and 0·2–0·3 m, but a significantly lower volume of small macropores (30–100 μm) at depths of 0–0·05, 0·05–0·1, 0·1–0·2 and 0·2–0·3 m. The volume of meso- (0·2–30 μm) and micro-pores (<0·2 μm) at different depths under the two tillage practices were similar. Tillage-induced changes in soil bulk density and pore-size volumes affected the ability of soil to fulfil essential soil functions in relation to organic matter turnover. Soil pore-size distribution, especially small macropores greatly affected LLWR and there was a significant correlation between LLWR, which was calculated based on soil bulk density, and the proportion of small macropores. The proportion of small macropores were used to calculate LLWR instead of soil bulk density and the values for NT and MP soils ranged from 0·073 to 0·148 m3water/m3soil. Using the proportion of small macropores rather than bulk density in the calculation of LLWR resulted in more sensitive indications of SOC mineralization. Variation in the proportion of small macropores can help characterize the impacts of tillage practices on dynamics of LLWR and SOC sequestration.

scholarly journals SOIL QUALITY ATTRIBUTES RELATED TO URBANIZATION IN BRAZILIAN WATERSHED

2017 ◽  
Vol 25 (4) ◽  
pp. 317-328 ◽  
Author(s):  
Alexandre Marco da SILVA ◽  
Rodrigo Custodio URBAN ◽  
Luiz Augusto MANFRÉ ◽  
Michel BROSSARD ◽  
Marcelo Zacharias MOREIRA
Keyword(s):  
Ecosystem Services ◽  
Land Cover ◽  
Bulk Density ◽  
Soil Quality ◽  
Soil Bulk Density ◽  
Soil Samples ◽  
Subtropical Region ◽  
C Isotopes ◽  
Total Potential ◽  
Physical Chemical

In this study we investigated the variation of soil attributes according to urban-related land cover categories. The study was carried out in an urbanized watershed located in the Brazilian subtropical region (Sorocaba Municipality, São Paulo). Soil samples were collected considering the land cover category for analysis of physical, chemical and isotopic attributes. The land cover influenced the soils attributes. Soils from wooded and grassed areas presented significant differences, especially for values of C isotopes. Soil bulk density was significantly altered. According to considered land cover mosaic in the study, we estimated 10,241.28 tons of C stored in the thickness 20 cm of the watershed (whole area), and this amount is almost a half of the total potential of C storing in the watershed. We stress that projects of planned land cover should effectively implemented in urbanized regions to effectively contribute in storing more C and improving the soil-related ecosystem services.

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