Soil structure is a dynamic property affected by physical, chemical, and microbiological processes. Addition of organic matter to soils and the use of different management practices have been reported to impact soil s...Soil structure is a dynamic property affected by physical, chemical, and microbiological processes. Addition of organic matter to soils and the use of different management practices have been reported to impact soil structure and crop production. Moderation in soil temperature and increases in microbial activity and soil water retention are often suggested as reasons for the rise in crop yield when organic matter is added to the soil. Less is known about the direct effect of changes in soil structure on crop production. A field experiment was conducted to study the effect of summer cover crop and in-season management system on soil structure. The experiment was a nested design with summer cover crop as the main plot and management system as the subplot. Summer cover crop treatments included cowpea （Vigna unguiculata L. Walp.） incorporated into the soil in the fall （CI）, cowpea used as mulch in the fall （CM）, sudangrass （Sorghum vulgare） incorporated into the soil in the fall （S）, and dry fallow or bare ground （B）. Management systems were organic （ORG） and conventional （CNV） systems. Lettuce （Lactuca sativa L.） and cantaloupes （Cucumis melo L.） were cultivated in rotation in the plots for three consecutive years using the same cover crops and management systems for each plot. Disturbed and undisturbed soil cores were collected at the end of the third year and used for laboratory experiments to measure physical, chemical, and hy- draulic properties. Image analysis was used to quantify soil structure properties using a scanning electron micro- scope on thin sections prepared from the undisturbed soil cores. We found that total soil carbon was correlated with porosity, saturation percentage, and pore roughness. Pore roughness was correlated with crop production in gen- eral and with marketable production in particular. We found that the higher the complexity of the pore space, the more water retained in the soil, which may increase soil water residence and reduce plant water stress.展开更多
Natural soil variability is a well-known issue in geotechnical design,although not frequently managed in practice.When subsoil must be characterized in terms of mechanical properties for infrastructure design,random f...Natural soil variability is a well-known issue in geotechnical design,although not frequently managed in practice.When subsoil must be characterized in terms of mechanical properties for infrastructure design,random finite element method(RFEM)can be effectively adopted for shallow foundation design to gain a twofold purpose:(1)understanding how much the bearing capacity is affected by the spatial variability structure of soils,and(2)optimisation of the foundation dimension(i.e.width B).The present study focuses on calculating the bearing capacity of shallow foundations by RFEM in terms of undrained and drained conditions.The spatial variability structure of soil is characterized by the autocorrelation function and the scale of fluctuation(δ).The latter has been derived by geostatistical tools such as the ordinary Kriging(OK)approach based on 182 cone penetration tests(CPTs)performed in the alluvial plain in Bologna Province,Italy.Results show that the increase of the B/δratio not only reduces the bearing capacity uncertainty but also increases its mean value under drained conditions.Conversely,under the undrained condition,the autocorrelation function strongly affects the mean values of bearing capacity.Therefore,the authors advise caution when selecting the autocorrelation function model for describing the soil spatial variability structure and point out that undrained conditions are more affected by soil variability compared to the drained ones.展开更多
文摘Soil structure is a dynamic property affected by physical, chemical, and microbiological processes. Addition of organic matter to soils and the use of different management practices have been reported to impact soil structure and crop production. Moderation in soil temperature and increases in microbial activity and soil water retention are often suggested as reasons for the rise in crop yield when organic matter is added to the soil. Less is known about the direct effect of changes in soil structure on crop production. A field experiment was conducted to study the effect of summer cover crop and in-season management system on soil structure. The experiment was a nested design with summer cover crop as the main plot and management system as the subplot. Summer cover crop treatments included cowpea （Vigna unguiculata L. Walp.） incorporated into the soil in the fall （CI）, cowpea used as mulch in the fall （CM）, sudangrass （Sorghum vulgare） incorporated into the soil in the fall （S）, and dry fallow or bare ground （B）. Management systems were organic （ORG） and conventional （CNV） systems. Lettuce （Lactuca sativa L.） and cantaloupes （Cucumis melo L.） were cultivated in rotation in the plots for three consecutive years using the same cover crops and management systems for each plot. Disturbed and undisturbed soil cores were collected at the end of the third year and used for laboratory experiments to measure physical, chemical, and hy- draulic properties. Image analysis was used to quantify soil structure properties using a scanning electron micro- scope on thin sections prepared from the undisturbed soil cores. We found that total soil carbon was correlated with porosity, saturation percentage, and pore roughness. Pore roughness was correlated with crop production in gen- eral and with marketable production in particular. We found that the higher the complexity of the pore space, the more water retained in the soil, which may increase soil water residence and reduce plant water stress.
文摘Natural soil variability is a well-known issue in geotechnical design,although not frequently managed in practice.When subsoil must be characterized in terms of mechanical properties for infrastructure design,random finite element method(RFEM)can be effectively adopted for shallow foundation design to gain a twofold purpose:(1)understanding how much the bearing capacity is affected by the spatial variability structure of soils,and(2)optimisation of the foundation dimension(i.e.width B).The present study focuses on calculating the bearing capacity of shallow foundations by RFEM in terms of undrained and drained conditions.The spatial variability structure of soil is characterized by the autocorrelation function and the scale of fluctuation(δ).The latter has been derived by geostatistical tools such as the ordinary Kriging(OK)approach based on 182 cone penetration tests(CPTs)performed in the alluvial plain in Bologna Province,Italy.Results show that the increase of the B/δratio not only reduces the bearing capacity uncertainty but also increases its mean value under drained conditions.Conversely,under the undrained condition,the autocorrelation function strongly affects the mean values of bearing capacity.Therefore,the authors advise caution when selecting the autocorrelation function model for describing the soil spatial variability structure and point out that undrained conditions are more affected by soil variability compared to the drained ones.
