中国土壤有机质含量变异性与空间尺度的关系

以中国土种志资料为基础,分析了土壤有机质含量变异与空间尺度的关系及土类内和土类间的变异程度,探讨了不同空间尺度单元下,土壤有机质平均含量与土壤性质的相关性。结果表明,以土壤剖面为单元,随着土壤剖面数的增加,土壤有机质含量的变异系数增大;行政区域尺度单元内部土壤有机质变异程度大于单元间土壤有机质含量的变异程度。以土壤分类单元为空间单元,土类内的有机质含量变异程度小于土类间的变异程度。随着统计单元空间尺度的增大,土壤有机质含量与土壤性质之间的相关性减弱。因此,采用网格法或行政区划分空间区域,获得空间区域单元内土壤有机质含量或贮量的精确估算需要较多的剖面,但外推至数据不足的空间区域时,估算的不确定较小;采用土壤分类单元为空间区域单元,结果则相反。     

波浪作用下成层海床孔隙水压力响应的简化分析

采用不排水条件下孔隙水压力发展模式,作为Terzagh i一维固结方程中考虑波浪循环作用所引起的孔隙水压力源项,对于成层海床建立了推广的一维动力固结方程,运用数理方程中的分离变量法与G reen函数求解了成层海床在波浪作用下残余孔隙水压力的发展规律,进而对成层海床的液化势进行了评判。对比计算与分析表明,海床表层土的渗透性及其厚度对于海床的整体抗液化性能具有显著的影响,低渗透性的表层导致海床孔隙水压力的显著积累,此时表层置换法是防治液化的有效途径。     

长输管道抗震研究的新进展

本文主要从以下4个方面:地震对长输管道的危害、长输管道震害的研究方法、管道抗震分析和管道抗震的措施,介绍了近几年长输管道抗震方面的研究进展,指出了今后长输管道的研究方向。     

鲁西枣庄-临沂地区新元古界震碛岩的主要特征

鲁西枣庄—临沂地区新元古界碳酸盐岩系中,发育有由地震造成的同沉积构造现象,如微晶方解石脉、层内变形褶曲、层内微断层和内碎屑碳酸盐岩堆积等。野外实地观察、地质剖面测量和室内分析研究认为它们是由地震产生的强震动,使距震中一定范围的未固结沉积物经震动液化,震动变形形成的震积岩组合。根据其发育规律与组合特征,该地区震碛岩的形成应与古郯庐断裂在新元古代的活动密切相关。可初步确定为含有A、B和C3个震积岩单元的震动液化地震序列。     

利用气象要素计算五道梁地区土壤热流量的试验

根据五道梁地区1994—1997年的热流板测量土壤热流值,初步分析了该地区土壤热流随时间的变化特征。利用1994—1996年的月平均资料分别分析了总辐射、地表温度、地表温度和80 cm深度温度差和2 cm、10 cm深度的土壤热流的相关性,并建立了相应的回归方程;利用得到的回归方程对1997年的土壤热流作计算检验,就月平均资料来说,用总辐射和地温差来计算浅层土壤热流结果是比较可靠的。     

浅基础水平场地砂土液化危害性评价

分析了《建筑抗震设计规范》中砂土液化危害性评价方法的不足,通过确立液化土层在不同震害模式情况下的液化震陷计算值,建立了以震陷值S为指标的浅基础水平场地地基液化危害性评价等级,得到了其评价程序.     

土氡测量在海口市活动断层探测中的初步应用

运用土壤氡射气(土氡)测量方法对海口市的六条隐伏断层进行探测,检验土壤氡射气(土氡)测量在海口市地区的有效性,结果表明,土氡测量探测晚更新世(Q3)和全新世(Q4)隐伏断层具有较好的效果,可以作为海口市活动断层探测一种有效手段。     

Analysis of resistance factors for LRFD of soil nail pullout limit state using default FHWA load and resistance models

Abstract

Resistance factors for load and resistance factor design (LRFD) of pullout limit state of both permanent and temporary soil nails are calibrated against a wide design space using the current Federal Highway Administration (FHWA) nail load and resistance models. The calculated resistance factors were shown to scatter broadly among design scenarios that differ in wall face batter, soil friction angle, nail ultimate bond strength, and surcharge live load. An important lesson learned from the analysis results is that the current practice of using a single resistance factor for LRFD of nail pullout limit state could not result in uniform reliabilities across different design scenarios. Simple artificial neural network (ANN) models were developed for computation of resistance factors. Design examples demonstrated the ability of the ANN models in providing resistance factors that yield satisfactory and consistent reliabilities in different nail pullout designs.     

波浪作用下沉积物中氮、磷释放速率的试验研究

湖泊或海湾中的沉积物吸附氮(N)、磷(P)等元素所形成的沉积层成为水体富营养化的內源。在波浪作用下,尤其是强浪作用下,沉积物中的N、P会通过内源释放作用大量进入水体中。本文在自制的U型水槽中开展实验,采用不同水头差来模拟波浪的循环荷载作用,研究了沉积层中的N、P在静置固结状态(Ⅰ)、加波未液化状态(Ⅱ)、加波液化状态(Ⅲ)下的释放规律,并给出该试验条件下的沉积物释放速率的拟合方程。试验结果表明:沉积物中总氮(TN)和溶解性总氮(TDN)的释放速率会随着水动力作用的增强而增加;总磷(TP)、溶解性总磷(TDP)和活性磷酸盐(SRP)的释放速率也随着水动力作用增强而增加,但水体中悬浮物(SS)含量过高会限制其释放速率。     

Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data

Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.