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.

Water retention of arctic zone soils (Spitsbergen)

2013 ◽  
Vol 27 (4) ◽  
pp. 439-444 ◽  
Author(s):  
J. Melke ◽  
B. Witkowska-Walczak ◽  
P. Bartmiński
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Bulk Density ◽  
Size Distribution ◽  
Water Retention ◽  
Total Porosity ◽  
The Arctic ◽  
Arctic Zone ◽  
Retention Characteristics

Abstract The water retention characteristics of the arctic zone soils ((TurbicCryosol (Skeletic), TurbicCryosols (Siltic, Skeletic) and BrunicTurbicCryosol (Arenic)) derived in different micro-relief forms were determined. Water retention curves were similar in their course for the mud boils, cell forms, and sorted circles ie for TurbicCryosols. For these forms, the mud boils showed the highest water retention ability, whereas the sorted circles - the lowest one. Water retention curves for the tundra polygons (Brunic TurbicCryosol, Arenic) were substantially different from these mentioned above. The tundra polygons were characterized by the lowest bulk density of 1.26 g cm-3, whereas the sorted circles (TurbicCryosol, Skeletic) - the highest: 1.88 g cm-3. Total porosity was the highest for the tundra polygons (52.4 and 55.5%) and the lowest - for the sorted circles (28.8 and 26.2%). Pore size distribution of the investigated soils showed that independently of depths, the highest content of large and medium pores was noticed for the tundra polygons ie 21.2-24.2 and 19.9-18.7%, respectively. The lowest content of large pores was observed for the cell forms (6.4-5.9%) whereas the mud boils exhibited the lowest amount of medium sized pores (12.2-10.4%) (both TurbicCryosols Siltic, Skeletic). The highest content of small pores was detected in the mud boils - 20.4 and 19.0%.

scholarly journals Effect of tillage practices on least limiting water range in Northwest India

2017 ◽  
Vol 31 (2) ◽  
pp. 183-194 ◽  
Author(s):  
Meharban S. Kahlon ◽  
Karitika Chawla
Keyword(s):  
Bulk Density ◽  
Water Productivity ◽  
Critical Factor ◽  
Soil Bulk Density ◽  
Limiting Factor ◽  
No Tillage ◽  
Deep Tillage ◽  
Tillage Practices ◽  
Northwest India ◽  
Least Limiting Water Range

Abstract Tillage practices affect mechanical and hydrological characteristics of soil and subsequently the least limiting water range. This quality indicator under the wheat-maize system of northwest India has not been studied yet. The treatments included four tillage modes, namely conventional tillage, no-tillage without residue, no-tillage with residue, and deep tillage as well as three irrigation regimes based on the irrigation water and pan evaporation ratio i.e. 1.2, 0.9, and 0.6. The experiment was conducted in a split plot design with three replications. At the end of cropping system, the mean least limiting water range (m3 m-3) was found to be highest in deep tillage (0.26) and lowest in notillage without residue (0.15). The field capacity was a limiting factor for the upper range of the least limiting water range beyond soil bulk density 1.41 Mg m-3 and after that 10% air filled porosity played a major role. However, for the lower range, the permanent wilting point was a critical factor beyond soil bulk density 1.50 Mg m-3 and thereafter, the penetration resistance at 2 MPa becomes a limiting factor. Thus, deep tillage under compaction and no-tillage with residue under water stress is appropriate practice for achieving maximum crop and water productivity.

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;

The Influence on the Properties of Microporous Mullite of Adding Different Burning-Out Materials

2011 ◽  
Vol 214 ◽  
pp. 84-88
Author(s):  
Yu Bao Bi ◽  
Hui Fang Wang ◽  
Wei Lu
Keyword(s):  
Thermal Conductivity ◽  
High Temperature ◽  
Carbon Black ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Bulk Density ◽  
Size Distribution ◽  
Volume Stability ◽  
Uniform Microstructure ◽  
Industrial Alumina

Mullite has low thermal conductivity, advanced volume stability at high temperature, and is suit to prepare lightweight refractories. The micropored mullite aggregates has been produced by using industrial alumina and natural silica as starting materials, adding some burning-out materials, then fired at 1350°C for 6h. The influences on the bulk density, pore size distribution and microstructure of microporous mullite of adding these burning-out materials, such as carbon black, coke, and anthracite have been investigated. The conclusions are that the influences on the bulk density and microstructure of micropored mullite aggregates are significant. These three burning-out materials have a similar effect for the pore size distribution. The microporous mullite aggregates has the smallest bulk density and more uniform microstructure by using anthracite as the burning-out material.

pyGAPS: A Python-Based Framework for Adsorption Isotherm Processing and Material Characterisation

2019 ◽  
Author(s):  
Paul Iacomi ◽  
Philip L. Llewellyn
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Surface Area ◽  
Isosteric Heat ◽  
Material Characterisation ◽  
Mixture Adsorption ◽  
Surface Energetics ◽  
Adsorption Processing ◽  
User Friendly

Material characterisation through adsorption is a widely-used laboratory technique. The isotherms obtained through volumetric or gravimetric experiments impart insight through their features but can also be analysed to determine material characteristics such as specific surface area, pore size distribution, surface energetics, or used for predicting mixture adsorption. The pyGAPS (python General Adsorption Processing Suite) framework was developed to address the need for high-throughput processing of such adsorption data, independent of the origin, while also being capable of presenting individual results in a user-friendly manner. It contains many common characterisation methods such as: BET and Langmuir surface area, t and α plots, pore size distribution calculations (BJH, Dollimore-Heal, Horvath-Kawazoe, DFT/NLDFT kernel fitting), isosteric heat calculations, IAST calculations, isotherm modelling and more, as well as the ability to import and store data from Excel, CSV, JSON and sqlite databases. In this work, a description of the capabilities of pyGAPS is presented. The code is then be used in two case studies: a routine characterisation of a UiO-66(Zr) sample and in the processing of an adsorption dataset of a commercial carbon (Takeda 5A) for applications in gas separation.

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