辽宁沿海地区海洋经济增长质量空间特征及影响要素

在海洋经济质量转型之期,基于“认知—评价—建构—优化”理念,界定海洋经济增长质量内涵,通过中心-引力模型评价分析2000—2014年辽宁沿海地区海洋经济增长质量空间特征,构建了海洋经济增长质量模型,识别影响其空间特征的相关要素,并根据要素作用程度提出优化建议。研究发现：① 辽宁沿海地区海洋经济增长质量呈“核心—圈层”结构,形成以大连为“领头雁”的雁阵式相互继起模式;“钻石型”引力流结构促成辽宁沿海地区集中化连片发展格局;② 海洋经济增长质量空间特征主要受空间集聚效应影响,海洋资本、海洋基建和海洋产业结构成为推动海洋经济增长质量循环引力流的顺流机制,其中海洋产业结构成为影响辽宁海洋经济增长质量圈层空间集聚效应的关键流;海洋人才成为制约海洋经济增长质量循环引力流的逆流机制;③ 通过路径作用程度的象限划分,提出强化大连中心地职能,针对腹地城市定位及资源禀赋条件提出调控措施,推进沿海区域协调与一体化进程。     

基于孔隙率的延安黄土抗剪强度模型

孔隙率对黄土抗剪强度具有非常重要的影响,然而,孔隙率对黄土抗剪强度影响效果的认识并不充分。本文以陕西省延安黄土为研究对象,开展不同孔隙率的黄土直剪试验研究,探讨了孔隙率对粘聚力与内摩擦角的定量变化关系;并以此为基础,构建了基于孔隙率的延安黄土抗剪强度模型,并对其进行了验证。研究结果表明:(1)延安黄土粘聚力与孔隙率间呈幂函数变化关系;(2)延安不同孔隙率黄土内摩擦角取值呈现出两个区间,当孔隙率n≥0.4时,其内摩擦角在25±2.5°的范围内变动,而当孔隙率n<0.4时,其内摩擦角在29.5±2°的范围内变动;(3)通过分析得到了基于孔隙率的延安黄土抗剪强度模型,且该模型得到的黄土抗剪强度理论值与实测值间的误差较小,相对误差均在7%以内,具有较高的精确度。研究成果不仅能为延安黄土抗剪强度研究等提供技术支持,而且还能为该地区的工程建设等方面提供理论参考。     

茅山竹矿断层气定点观测场地勘选

拟在茅山断裂带沿线布设若干个断层气连续观测点,建组断层气观测网。以茅山竹矿地区为例,通过断层气测量的初步结果,结合地质、人工地震、跨断层短水准等多种手段联合分析研究区断层的活动性,从而确定断层气定点观测的点位,为组建断层气观测网的选点提供借鉴和参考。     

Predicting the entire soil-water characteristic curve using measurements within low suction range

The soil-water characteristic curve(SWCC) is widely used in the design and evaluation in the practice of geotechnical and geoenvironmental engineering such as the slope stability under the influence of environmental factors. The SWCC has distinct features in the capillary and adsorption zones due to different physical mechanisms. Measurements of the SWCC are typically limited within the capillary zone(i.e., low suction range). It is cumbersome and time-consuming to measure the SWCC in the adsorption zone(i.e., high suction range). This study presents a simple method to predict the entire SWCC within both the capillary and adsorption zones, using measured data only from low suction range(e.g., from 0 to 500 kPa). Experimental studies were performed on a completely weathered granite residual soil to determine its entire SWCC from saturated to dry conditions. The resultant SWCC, along with the SWCC measurements of 14 soils reported in the literature, were used to validate the proposed method. The results indicate that the proposed method has good consistency with a wide array of measured data used in this study. The proposed method is easy to use as it only requires a simple parameter calibration for a commonly used SWCC model. It can be used to improve the reliability in the prediction of the SWCC over the entire suction range when measurements are limited within the low suction range.     

GIS-based landslide susceptibility mapping using hybrid integration approaches of fractal dimension with index of entropy and support vector machine

The loess area in the northern part of Baoji City, Shaanxi Province, China is a region with frequently landslide occurrences. The main aim of this study is to quantitatively predict the extent of landslides using the index of entropy model(IOE), the support vector machine model(SVM) and two hybrid models namely the F-IOE model and the F-SVM model constructed by fractal dimension. First, a total of 179 landslides were identified and landslide inventory map was produced, with 70%(125) of the landslides which was optimized by 10-fold crossvalidation being used for training purpose and the remaining 30%(54) of landslides being used for validation purpose. Subsequently, slope angle, slope aspect, altitude, rainfall, plan curvature, distance to rivers, land use, distance to roads, distance to faults, normalized difference vegetation index(NDVI), lithology, and profile curvature were considered as landslide conditioning factors and all factor layers were resampled to a uniform resolution. Then the information gain ratio of each conditioning factors was evaluated. Next, the fractal dimension for each conditioning factors was calculated and the training dataset was used to build four landslide susceptibility models. In the end, the receiver operating characteristic(ROC) curves and three statistical indexes involving positive predictive rate(PPR), negative predictive rate(NPR) and accuracy(ACC) were applied to validate and compare the performance of these four models. The results showed that the F-SVM model had the highest PPR, NPR, ACC and AUC values for training and validation datasets, respectively, followed by the F-IOE model.Finally, it is concluded that the F-SVM model performed best in all models, the hybrid model built by fractal dimension has advantages than original model, and can provide reference for local landslide prevention and decision making.     

塔北地区寒武系白云岩储层裂缝充填特征与有效性

塔里木盆地寒武系白云岩储层具有年代老、埋深大、成岩作用强烈的特征,原生孔隙几乎被破坏殆尽,有效裂缝的发育程度是决定储层优劣的关键因素。根据岩芯描述、薄片鉴定、FMI成像测井、扫描电镜、阴极发光、电子探针以及流体包裹体分析等研究手段,开展了塔里木盆地北部地区(简称"塔北地区")寒武系白云岩储层的裂缝充填特征及有效性分析。塔北地区整体裂缝发育,天山南地区与塔河地区裂缝在产状、线密度、形态以及充填特征上存在差异。天山南地区裂缝线密度与有效性均低于塔河地区,充填矿物主要为自形白云石与石英,其次为方解石、石膏与黄铁矿。充填白云石分为3期,对应的温度区间分别为70℃～90℃、90℃～110℃及110℃以上,均为地层内的成岩流体成因;充填石英分两期,第一期为黏土矿物转化蚀变形成,第二期可能为热液成因。塔河地区裂缝线密度高,有效性较好,溶蚀作用发育,是有利的勘探地区,其充填物以热液矿物组合形式出现,主要为方解石,其次为石膏、鞍状白云石、黏土矿物、沥青等,重晶石以交代白云石的形式出现。充填方解石分为4期,对应的温度区间分别为70℃～100℃、100℃～130℃、130℃～180℃及180℃以上,前3期充填为不同埋深时期地层内成岩流体成因,最后一期充填为自下部运移而来的高温热液流体成因。     

Monte Carlo simulation of scintillation crystal detector for formation element logging

Formation elements logging is a neutron gamma spectroscopy logging technique used to acquire the content of elements and minerals by recording the gamma ray produced by the reaction of neutron and elemental nucleus in the formation. It has a wide usage in discriminating complex lithology and evaluating unconventional reservoir. The Monte Carlo simulation model of formation elements logging tool is established in this paper, with which the effects of tool parameters including the material and length of the scintillation crystal and source spacing on logging responses are modeled. The results show that the energy response of LaBr_3: Ce crystal is better than others, and the detection efficiency increases with the crystal length but decrease with source spacing. The above results may be used as a reference for optimizing the tool structure design.     

中国碳强度关键影响因子的机器学习识别及其演进

碳强度影响因子数量众多,通过在众多因子中评估其重要性以识别出关键影响因子进而解析碳强度关键因子的变化规律,是中国2030年碳强度能否实现比2005年下降60%~65%目标的科学基础。传统的回归分析方法对于评估众多因子的重要性存在多重共线性等问题,而机器学习处理海量数据则具有较好的稳健性等优点。本文从能源结构、产业结构、技术进步和居民消费等方面选取了56个中国碳强度影响因子指标,采用随机森林算法基于信息熵评估了1980-2014年逐年各项因子的重要性,通过指标数量与信息熵的对应关系统一筛选出每年重要性最大的前22个指标作为相应年度关键影响因子,最终依据关键影响因子的变化趋势划分了3个阶段作了演进分析。结果发现：1980-1991年,碳强度的关键因子主要以高耗能产业规模及占比、化石能源占比和技术进步为主;1992-2007年,中国经济进入快车道增长时期,服务业占比和化石能源价格对碳强度的影响作用开始显现,居民传统消费的影响作用在增大;2008年全球金融危机后,中国进入经济结构深化调整时期,节能减排力度大大增强,新能源占比和居民新兴消费的影响作用迅速显现。为实现2030年碳强度下降60%~65%目标,优化能源结构和产业结构,促进技术进步,提倡绿色消费,强化政策调控是未来需要采取的主要措施。     

Seasonal response of surface wind to SST perturbation in the Northern Hemisphere

The seasonal response of surface wind speed to sea surface temperature(SST)change in the Northern Hemisphere was investigated using 10 years(2002-2011)high-resolution satellite observations and reanalysis data.The results showed that correlation between surface wind speed perturbations and SST perturbations exhibits remarkable seasonal variation,with more positive correlation is stronger in the cold seasons than in the warm seasons.This seasonality in a positive correlation between SST and surface wind speed is attributable primarily to seasonal changes of oceanic and atmospheric background conditions in frontal regions.The mean SST gradient and the prevailing surface winds are strong in winter and weak in summer.Additionally,the eddy-induced response of surface wind speed is stronger in winter than in summer,although the locations and numbers of mesoscale eddies do not show obvious seasonal features.The response of surface wind speed is apparently due to stability and mixing within the marine atmospheric boundary layer(MABL),modulated by SST perturbations.In the cold seasons,the stronger positive(negative)SST perturbations are easier to increase(decrease)the MABL height and trigger(suppress)momentum vertical mixing,contributing to the positive correlation between SST and surface wind speed.In comparison,SST perturbations are relatively weak in the warm seasons,resulting in a weak response of surface wind speed to SST changes.This result holds for each individual region with energetic eddy activity in the Northern Hemisphere.     

利用稳定同位素(15N)示踪技术研究浮游藻类氮素吸收速率特征

浮游藻类对溶解态氮的吸收同化是湖泊氮生物循环和水体富营养化发生机制探讨的关键环节。本文通过~(15)N稳定同位素添加实验以铜绿微囊藻(Microcystis aeruginosa)、海链藻(Thalassiosira sp.)、卡德藻(Tetraselmis sp.)、剧毒卡尔藻(Karlodinium veneficum)以及盐水隐藻(Rhodomonas salina)为研究对象,从浮游藻类氮素吸收时间、营养盐基质以及藻种差异三个方面研究五种藻类对铵氮(NH_4~+-N)、硝氮(NO_3~--N)、尿素氮(Urea-N)三种形态氮的吸收特征。研究发现:(1)浮游藻类对三种形态氮的吸收均在1h时吸收速率最高,其氮素吸收过程为快速吸收。(2)浮游藻类优先吸收还原态氮,其中NH_4~+-N吸收速率最高,当培养周期为1d和4d时浮游藻类对NH_4~+-N吸收速率的均值分别为4.05和4.15μmol/(L·h);浮游藻类对Urea-N吸收相对偏好系数为25.18—713.42,表现出对小分子溶解态有机氮的特定偏好性。(3)不同藻种对氮素吸收具有不同特征,其中,剧毒卡尔藻对三种形态氮的吸收速率均为最高,而铜绿微囊藻的吸收速率均为最低;不同藻种不同培养时间氮素吸收速率差异与浮游藻类生长周期等特性有关。不同浮游藻类对不同形态氮素表现出吸收特异性,对水体氮负荷和浮游藻类水华优势种形成将产生重要影响。