三江平原西部土壤硒分布特征及其影响因素

近年来在黑龙江三江平原局部地区发现有珍贵的富硒土地,但对三江平原土壤硒的分布以及土壤硒含量的控制因素研究较少.三江平原西部地区土地质量地球化学调查发现,该区表层土壤主要以足硒为主,未见硒中毒土壤,富硒土壤主要分布于完达山山前至沿挠力河之间的冲湖积低平原地区,少量分布于萝北县城北部的湖成剥蚀台地,硒不足或硒潜在不足地区主...     

水对土质边坡的稳定性影响分析

首先论述了地下水对边坡稳定性的影响因素,水对土质边坡的影响作用,接着推导出了考虑水作用影响的边坡安全系数计算公式,最后指出应用动态的观点来研究边坡体内的地下水作用.     

生物土壤结皮固沙理论与实践

生物土壤结皮是由土壤微生物、藻类、地衣和苔藓等孢子植物类群与土壤颗粒形成的有机复合体,在全球干旱区地表广泛分布,是干旱地表生物覆被层的主要构建者.生物土壤结皮是荒漠植物群落演替的先锋类群,能够提高荒漠地表的稳定性,固定碳和氮等营养元素,增加土壤肥力,并在保持土壤水分方面发挥重要作用,因此在干旱区受损地表的生态修复方面具...     

某长江大桥深度超过15米的砂土层液化势的综合评价

不同抗震设计规范的砂土液化判别方法或国内外其他有代表性的液化判别方法所采用的地震动参数和土性指标及其埋藏条件是不同的,因而采用这些方法对同一工程场地进行液化势预测时其评价结果通常有一些差异,甚至会得到相反的结论。为了给重大工程建设提供较为合理、可信的地基液化势预测结果,采用多种液化判别方法进行场地液化势的综合评价是比较客观的,也是必要的。本文结合某长江大桥桥基工程,采用建筑抗震设计规范的砂土液化判别方法、国内外有代表性的液化判别方法、有限元数值分析法等多种方法逐一对该工程场地砂性土层进行液化判别,并结合室内动三轴液化试验结果,对主桥墩不考虑冲刷条件和考虑一般冲刷深度5m条件时的砂性土层进行了液化势的综合评价,并将各土层的液化势分为液化、可能液化和不液化3个等级,得到了较为合理可靠的判别结果。     

饱和砂性土流变模型的试验研究

正确合理的土体本构模型确定是地面沉降模拟的关键之一。上海和江苏地区多年来野外分层标的实际观测资料表明该区含水层系统砂层变形具有流变特征,表现出变形滞后于含水层水位变化的现象。本文基于粘弹性理论,选取了常州含水层系统原状砂性土样进行单轴压缩试验,分析了砂性土流变荷载曲线,并选择现有的相关本构模型进行识别,从而确定能更好反映研究区土体变形规律的流变模型。结果表明,研究区砂性土可采用Burgers模型进行描述,反演获得的4个流变参数随荷载的增加表现出一定的规律性。     

荆门热电厂厂区膨胀土等级的可拓评价研究

运用可拓学的基本理论,建立了膨胀土可拓评价模型。以此模型为基础,对荆门热电厂的膨胀土进行了可拓综合评价,并将判别结果与分级膨胀量评价法的判别结果进行了对比,其结果是一致的,说明该方法是可行的。     

Spatial variation and driving mechanism of soil organic carbon components in the alluvial/sedimentary zone of the Yellow River

Alluviation and sedimentation of the Yellow River are important factors influencing the surface soil structure and organic carbon content in its lower reaches. Selecting Kaifeng and Zhoukou as typical cases of the Yellow River flooding area, the field survey, soil sample collection, laboratory experiment and Geographic Information System(GIS) spatial analysis methods were applied to study the spatial distribution characteristics and change mechanism of organic carbon components at different soil depths. The results revealed that the soil total organic carbon(TOC), active organic carbon(AOC) and nonactive organic carbon(NOC) contents ranged from 0.05–30.03 g/kg, 0.01–8.86 g/kg and 0.02–23.36 g/kg, respectively. The TOC, AOC and NOC contents in the surface soil layer were obviously higher than those in the lower soil layer, and the sequence of the content and change range within a single layer was TOCNOCAOC. Geostatistical analysis indicated that the TOC, AOC and NOC contents were commonly influenced by structural and random factors, and the influence magnitudes of these two factors were similar. The overall spatial trends of TOC, AOC and NOC remained relatively consistent from the 0–20 cm layer to the 20–100 cm layer, and the transition between high-and low-value areas was obvious, while the spatial variance was high. The AOC and NOC contents and spatial distribution better reflected TOC spatial variation and carbon accumulation areas. The distribution and depth of the sediment, agricultural land-use type, cropping system, fertilization method, tillage process and cultivation history were the main factors impacting the spatial variation in the soil organic carbon(SOC) components. Therefore, increasing the organic matter content, straw return, applying organic manure, adding exogenous particulate matter and conservation tillage are effective measures to improve the soil quality and attain sustainable agricultural development in the alluvial/sedimentary zone of the Yellow River.     

Validation of a soil water balance model using soil water content and pressure head data

The validation of soil water balance models and the evaluation of the quality of the model predictions at field‐scale require time‐series of in situ measured model outputs. In our study, we have validated such a model using a 6‐year period with time‐series of automatically recorded, daily volumetric soil water contents measured with the time‐domain reflectometry with intelligent microelements (TRIME) method and daily pressure heads measured with tensiometers. The comparisons of simulated with measured soil water contents and pressure heads were analysed using the modelling efficiency index (IA) and the square root of the mean square error (RMSE) in order to evaluate the prediction quality of the model. In our study, IA and RMSE, obtained either from the comparison of simulated with measured soil water contents or the comparison of calculated with observed pressure heads, in some cases lead to different results regarding the evaluation of the simulation quality of the soil water balance model. For example, a good fit between simulated and observed soil water contents does not necessarily result in a comparably good fit between the corresponding calculated and measured pressure heads. Therefore, a combined use of both measurement techniques, which takes into account their respective advantages and disadvantages, gives a more complete overview on the simulation quality of the soil water balance model than the single use of one of those techniques. Copyright © 2004 John Wiley & Sons, Ltd.     

A coupling method for soil structure interaction problems

This paper describes a soil‐structure coupling method to simulate blast loading in soil and structure response. For the last decade, simulation of soil behavior under blast loading and its interaction with semi buried structure in soil becomes the focus of computational engineering in civil and mechanical engineering communities. In current design practice, soil‐structure interaction analysis often assumes linear elastic properties of the soil and uses small displacement theory. However, there are numerous problems, which require a more advanced approach that account for soil‐structure interaction and appropriate constitutive models for soil. In simplified approaches, the effect of soil on structure is considered using spring‐dashpot‐mass system, and the blast loading is modeled using linearly decaying pressure–time history based on equivalent trinitrotoluene and standoff distance, using ConWep, a computer program based on semi‐empirical equations. This strategy is very efficient from a CPU time computing point of view but may not provide accurate results for the dynamic response of the structure, because of its significant limitations, mainly when soil behavior is strongly nonlinear and when the buried charge is close to the structure. In this paper, both soil and explosive are modeled using solid elements with a constitutive material law for soil, and a Jones–Wilkins–Lee equation of state for explosive. One of the problems we have encountered when solving fluid structure interaction problems is the high mesh distortion at the contact interface because of high fluid nodal displacements and velocities. Similar problems have been encountered in soil structure interaction problems. To prevent high mesh distortion for soil, a new coupling algorithm is performed at the soil structure interface for structure loading. The coupling method is commonly used for fluid structure interaction problems in automotive and aerospace industry for fuel sloshing tank, and bird impact problems, but rarely used for soil structure interaction problems, where Lagrangian contact type algorithms are still dominant. Copyright © 2012 John Wiley & Sons, Ltd.