Soil Aggregation and Its Relationship with Organic Carbon of Purple Soils in the Sichuan Basin,China

The interaction of soil aggregate dynamics with soil organic carbon is complex with varied spatio-temporal processes in macro-and micro-aggregates. This paper is to determine the aggregation of soil aggregates in purple soils （Regosols in FAO Taxonomy or Entisols in USDA Taxonomy） for four types of land use, cropland [corn （Zea mays L.）], orchard （citrus）, forestland （bamboo or cypress）, and barren land （wild grass）, and to explore their relationship with soil organic carbon in the Sichuan basin of southwestern China. Procedures and methods, including manual dry sieving procedure, Yoder＇s wet sieving procedure, pyrophosphates solution method, and Kachisky method, are used to acquire dry, wet, and chemically stable aggregates, and microaggregates. Light and heavy fractions of soil organic carbon were separated using 2.0 g·mL^-1 HgI2-KI mixed solution. The loosely, stably, and tightly combined organic carbon in heavy fraction were separated by extraction with 0.1 M NaOH and 0.1 M NaOH-0.1M Na4P2O7 mixed solution （pH 13）. The results show that the contents of dry and wet macroaggregates 〉0.25 mm in diameter were 974.1 and 900.0 g·kg^-1 highest in red brown purple soils under forestland, while 889.6 and 350.6 g·kg^-1 lowest in dark purple soil and lowest in grey brown purple soils under cropland, respectively. The chemical stability of macroaggregates was lowest in grey brown purple soil with 8.47% under cropland, and highest in red brown purple soil with 69.34% under barren land. The content of microaggregates in dark purple soils was 587g·kg^-1 higher than brown purple soils, while 655g·kg^-1 in red brown purple soils was similar to grey brown purple soils （651g·kg^-1）. Cropland conditions, only 38.4% of organic carbon was of the combined form, and 61.6% of that existed in light fraction. Forestland conditions, 90.7% of organic carbon in red brown purple soil was complexed with minerals as a form of humic substances. The contents and stability of wet aggregates 〉 0.25 mm, contents and stability of chemically stable aggregates 〉0.25 mm, contents of microaggregates 〉 0.01 mm, contents of aggregated primary particle （d〈0.01 mm） and degree of primary particles （d 〈0.01 mm） aggregation were closely related to the concentrations of total soil organic carbon, and loosely and tightly combined organic carbon in heavy fraction. Soil microaggregation could be associated with organic carbon concentration and its combined forms in heavy fraction. There was a direct relationship between microaggregation and macroaggregation of soil primary particles, because the contents of wet aggregates 〉 0.25 mm and its water stability of aggregates were highly correlated with the contents of aggregated primary particle （d 〈 0.01 mm） and the degree of primary particles （d 〈 0.01 mm） aggregation.

A Method of Assessing Parameters of Air-Void Structure in Air-Entrained Concretes

The air-void size distribution and number of air voids are crucial characteristics of air-entrainment. The standard spacing factor L is based on the Powers model, in which considerable simplifications are assumed. A better solution is provided by the Philleo factor, which determines the percentage content of protected paste located at a distance S from the edge of the nearest air void. Developing the concept put forward by Philleo, a method of determining the volume of protected paste on the basis of images generated from the numerical model of concrete grain structure including layout of aggregate-paste-air, is proposed. It is the ratio of the volume of the paste protected by air voids to the total paste volume. The PPV （protected paste volume） index accounts not only for sizes and number of air voids, but also for the role of aggregate particles in the placement of these pores, which is often disregarded in analyses. The PPV results obtained from image analysis were compared with standard spacing factor L and with the parameter developed by Philleo. The analyses conducted by the authors shows that accounting for aggregate grains in calculations substantially affects the assessment of the quality of the air-pore structure.

Effects of land use patterns on soil aggregate stability in Sichuan Basin,China

Soil aggregate stability as a key indicator of soil structure, is a product of interactions between soil environment, management practices, and land use patterns. The objective of this study was to analyze the impact of various land use patterns on soil aggregate stability in Sichuan Basin of southwestern China. The dry- and water-stable aggregate size distributions were determined by manual dry sieving procedure and Yoder＇s wet sieving procedure, respectively, while microaggregates and its mechanical and chemical stabilities by Kachisky＇s method, oscillator method, and citrate-dithionate （C-D） reagent method, separately. The results indicated that fractal dimension and surface fractal dimension were useful indicators to reflect soil aggregate distribution. Land use patterns have an obvious influence on soil aggregate stability. In the study area, water stability, mechanical stability, and chemical stability followed the sequence, Barren land 〉 forestland 〉 orchard 〉 cropland, and the original stability and collapse velocity were sensitive to soil properties and soil structure. The difference of aggregate stability under different land use patterns is mainly due to the intensity of human disturbance and cultivation. Improper land use patterns will lead to breakdown of unstable aggregates, producing finer and more-easily transportable particles and microaggregates. In the future, inappropriate cultivation and land use patterns should be changed to protect soil structure, to improve soil aggregate stability and soil fertility in Sichuan Basin.

Estimating Water Retention with Pedotransfer Functions Using Multi-Objective Group Method of Data Handling and ANNs

Pedotransfer functions （PTFs） have been developed to estimate soil water retention curves （SWRC） by various techniques. In this study PTFs were developed to estimate the parameters （θs, θr, α and λ） of the Brooks and Corey model from a data set of 148 samples. Particle and aggregate size distribution fractal parameters （PSDFPs and ASDFPs, respectively） were computed from three fractal models for either particle or aggregate size distribution. The most effective model in each group was determined by sensitivity analysis. Along with the other variables, the selected fractal parameters were employed to estimate SWRC using multi-objective group method of data handling （mGMDH） and different topologies of artificial neural networks （ANNs）. The architecture of ANNs for parametric PTFs was different regarding the type of ANN, output layer transfer functions and the number of hidden neurons. Each parameter was estimated using four PTFs by the hierarchical entering of input variables in the PTFs. The inclusion of PSDFPs in the list of inputs improved the accuracy and reliability of parametric PTFs with the exception of ~s- The textural fraction variables in PTF1 for the estimation of a were replaced with PSDFPs in PTF3. The use of ASDFPs as inputs significantly improved a estimates in the model. This result highlights the importance of ASDFPs in developing parametric PTFs. The mCMDH technique performed significantly better than ANNs in most PTFs.