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。     

莱州湾海水中营养盐分布与富营养化的关系

根据2001年5月和9月2个航次莱州湾海区海水营养盐等的调查资料,分析了该海域海水中5项营养盐的分布特征及时空变化,评价了水质的富营养化状况。结果表明,溶解无机氮的平均浓度为9.80μmol/dm3,2个季节中溶解无机氮以NO3-N浓度为最高,平均为7.61μmol/dm3,占总无机氮的77.65%,是莱州湾海水中的无机氮主要形式;活性磷酸盐的平均浓度为0.48μmol/dm3,活性硅酸盐的平均浓度为11.31μmol/dm3。研究发现,莱州湾海水中溶解无机氮和活性磷酸盐浓度分别是12 a前的2.03倍和3.2倍。DIN∶P,Si∶P,Si∶DIN比值分别为69.5,34.2,1.4;因此,磷酸盐为限制因素。按照营养状态指数值,莱州湾海区湾顶近岸海域划分为富营养化区,秋季一旦水文气象等条件适宜有发生赤潮的可能。     

Pore-water distribution and quantification of diffusive benthic fluxes of nutrients in the Huanghai and East China Seas sediments

1 Indroduction The coastal zone and continental shelf area is an important region in the global biogeochemical cycle of nutrients in the ocean. This portion of the global ocean interacts closely with the continents, atmosphere and the open ocean in a comp…     

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.     

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.     

基于吸力量测确定膨胀土活动带和裂隙深度

采用M itchell公式和裂隙扩展深度方程两种吸力法确定安康地区膨胀土大气影响深度和裂隙开展深度。其一通过对安康地区两处天然边坡开挖观测井,利用张力计进行不同深度处吸力值的现场量测,根据M itchell提出公式计算大气影响深度;其二根据非饱和土抗拉强度公式,建立膨胀土裂隙扩展深度方程,利用基质吸力量测结果求其理论解。结果表明,安康地区膨胀土吸力变化曲线随深度增加变幅减小,呈波浪式推移。M itchell公式确定安康地区膨胀土的大气影响深度为3.35m以内,裂隙深度方程确定裂隙开展深度为3.063.14m。利用M itchell公式计算大气影响深度与膨胀土断裂理论公式确定的裂隙开展深度结果接近。     

土结构性本构模型研究现状综述

土本构模型的建立是一个重要而又复杂的问题,到目前为止,国内外学者们已提出数以百计的土本构模型,诸多文献也对这些模型进行了评述和归纳。然而这些土本构模型多是在扰动土或砂土的基础上发展和建立起来的,它们难以描述由于土结构性引起的各种非线性行为,其计算结果与实际情况相差甚远。天然土体一般都具有一定的结构性,所以有必要建立考虑土结构性影响的土本构模型。针对这个现实,目前有些学者已基于各种理论和方法,提出了一些可以考虑土结构性影响的土本构模型,并得了较好的应用。但在目前的文献中还很少有对土的结构性本构模型研究进行归纳,基于此,本文简要介绍了一下目前土的结构性本构模型研究现状,并提出了这些本构模型在应用中所存在的问题。     

广西农业干旱动态评估模型

以自然条件下大气-作物-土壤系统的水量平衡方程为基础,结合广西干旱灾害特点,建立广西农业干旱评估模型。与广西历史农业旱情实况对比分析表明,该模型能够较客观、定量地对农业干旱的发生、发展过程进行逐日动态监测和灾中、灾后评估。     

Understanding the Past and Present and Predicting the Future: Farmers’ Use of Multiple Nutrient Best Management Practices in the Upper Midwest

Understanding what drives farmers’ voluntary adoption of nutrient and soil best management practices has important consequences for many environmental outcomes including water quality. We build on research revealing the need for simultaneous use of multiple nitrogen best management practices to achieve water quality improvement goals. Using social, economic and attitudinal variables we predict the use of multiple nitrogen best management practices at three time points: current use (2013), past use (before 2013), and likelihood of use on their largest field in the next three years. Our empirical analysis uses structural equation modeling with latent variables and 2014 farmer survey data from three Midwestern US states. Most farmers in our sample used at least one of the six best management practices. Our results reveal that farmers’ attitudes, use of information sources, and conservation program participation affect the number of nitrogen best management practices concurrently in use at multiple time points.     

土壤粒径的光谱响应特性研究

以实验室制备的5个不同粒径水平的土壤样本和室内高光谱数据为基础,通过对光谱数据进行重采样、数学变换等预处理并进行单因素方差分析、相关性分析和回归分析,探讨土壤粒径的高光谱特性,建立了光谱数据预测土壤粒径的校正模型。结果表明,土壤粒径对反射光谱有显著的影响,波长越长影响越大;在全波段范围内土壤粒径和光谱数据都呈负相关关系,对原始光谱数据进行微分变换能增加其与土壤粒径的相关性;以反射率一阶微分建立的回归模型为反演土壤粒径的最佳模型,其建模决定系数■、预测决定系数■、预测相对偏差RPD分别为0.666,0.653,2.043,预测均方根误差RMSE为0.175。