CMIP5地球系统模式溶解氧模拟结果分析

本文基于常用的统计方法,通过与WOA09观测的海洋溶解氧浓度数据进行比较,定量地评估了9个CMIP5地球系统模式在历史排放试验中海洋溶解氧气候态特征的模拟能力。在海表,由于地球系统模式均能很好地模拟海表温度（SST）,模式模拟的海表溶解氧浓度分布与观测一致,模拟结果无论是全球平均浓度偏差还是均方根误差均接近0,空间相关系数与标准偏差接近1。在海洋中层以及深层这些重要水团所在的区域,各模式的模拟能力则差异较大,尤其在溶解氧低值区（OMZs）所在的500m到1000m,各模式均出现全球平均偏差、均方根误差的极大值以及空间相关系数的极小值。在海洋内部,模式偏差的原因比较复杂。经向翻转环流和颗粒有机碳通量均对模式的偏差有贡献。分析结果表明物理场偏差对溶解氧偏差的贡献较大。一些重要水团,比如北大西洋深水,南极底层水以及北太平洋中层水在极大程度上影响了溶解氧在这些海区的分布。需要指出的是,虽然在海洋内部各模式模拟的溶解氧浓度偏差较大,但是多模式平均结果却能表现出与观测较好的一致性。     

中国人口城镇化质量评价及省际差异分析

新型城镇化是中国的重要国策,对人的城镇(市)化的科学评价是正确认识城镇化和制定相关政策的重要基础.目前城--乡二元分析框架下的以城镇化率和城镇(或区域)城镇化质量为主的评价方法,难以反映城镇化过程中社会结构的变化,同时乡村人口的城镇化发展也被忽略.本文提出人口城镇化质量的概念,建立了衡量人口城镇化质量的指标体系.对1995,2000,2005,2010和2012年全国及各省市的城镇人口,乡村人口及总人口的城镇化质量进行了分析.研究发现:① 尽管城镇人口的城镇化速度显著快于乡村人口,但城镇化并非城镇人口独有的社会过程.② 城乡两类人口的城镇化质量在省域尺度上正逐步形成差异明显的空间格局.③ 北京,上海,浙江等少数省市乡村人口的城镇化质量已经超越部分内地省市城镇人口的城镇化质量.建议更新对城镇化的认识和评价标准,探索在城镇化发达的地区调整城--乡二元体制的新途径,促进中国城镇化的健康发展.     

Aspects of reproduction of the brown mussel Perna perna at the Iture rocky beach near Cape Coast,Ghana

Aspects of the reproductive biology of the brown mussel Perna perna at the Iture rocky beach near Cape Coast, Ghana, were studied from September 2014 to August 2015. The current study was aimed at providing information useful for managing the mussel fishery in this locality and also that would form the basis for designing appropriate culture methods for the species. Microscopic examination of fresh smears of gonadal material, as well as histological preparations of the gonad, were used to study the sexuality and breeding pattern of the species. Monthly gonadal and condition indices were also determined. Perna perna exhibited gonochoristic sexuality with a sex ratio of approximately 1:1 throughout the study period. Sexes were identifiable at shell lengths of 15.0–19.9 mm. Five stages of gonadal development were identified in both sexes. Gametogenic activity was continuous throughout the year, with two major spawning activities, from April to June and from August to December. These periods coincided with the major and minor rainy seasons, respectively, as well as the major upwelling period in August. Condition indices suggest that the mussels were in better condition for harvesting in March and August prior to the major spawning events.     

Electrical analogy for modelling thermal regime and moisture distribution in sandy soils

The soil mass is subjected to temperature variation due to several human activities (viz. tanks storing heated fluids, buried cables and pipelines, air-conditioning ducts, disposal of nuclear and thermal power plant wastes etc.), which result in heat-induced migration of the moisture in it. Though several studies have been conducted in the past to investigate the mechanism of heat migration through the soil mass, a methodology for ‘real-time measurement of the variations in temperature, flux and moving moisture front, in tandem, with respect to space' has rarely been attempted. In this context, extensive laboratory investigations were conducted to measure real-time flux and temperature variations in the sandy soils, and the validation of results has been done by employing an equivalent electrical circuit programme, LTspice. Subsequently, a mathematical model PHITMDS (i.e. Prediction of Heat-Induced Temperature and Moisture Distribution in Soil) has been developed and its utility and efficacy, for predicting the depth-wise temperature and heat-induced moisture migration, due to evaporation, in terms of position of moving moisture front in the sandy soil has been critically discussed and demonstrated.     

扬子地台东南缘下寒武统清虚洞组风暴沉积特征及其重要意义

在扬子地台东南缘,下寒武统龙王庙阶清虚洞组主要由浅水碳酸盐岩组成。在野外露头剖面实测和室内镜下薄片观察的基础上,大量风暴沉积被发现于不同剖面清虚洞组的不同层位中,同时大量风暴诱发形成的沉积构造被识别出来,包括侵蚀基底、粗粒滞留沉积、粒序层理、平行层理、丘状交错层理(少见并且值得怀疑)以及沙纹层理,组成了多种类型的风暴沉积序列。结合更靠扬子东南缘的深水剖面中重力流沉积的缺乏,可以推断早寒武世龙王庙期扬子地台的沉积模式为碳酸盐缓坡。结合风暴的形成机制以及清虚洞组风暴沉积的发育特征(尤其是粗粒滞留砾屑的定向排列和典型丘状交错层理的缺乏),可以推断研究区风暴沉积形成于强烈的冬季风暴作用,并且早寒武世龙王庙期华南的古地理位置应当位于中纬度地区,这一结论对一些著名的全球古地理重建方案提出了质疑。同时中纬度地区大规模发育蒸发岩和碳酸盐岩还佐证了寒武纪地球处于热室(Hothouse)时期。     

渝东南地区下寒武统牛蹄塘组页岩孔径分布测试方法研究

低温氮气吸附法已普遍用于评价页岩的孔隙结构,但是文献中报道的脱气温度和脱气时间等测试条件不尽相同,此外测试结果中经常出现滞后环不闭合的情况,严重影响了孔径分布等结构参数测试的准确性。为了评价和探索有效的页岩孔径分布测试方法,本文选取渝科1井下寒武统牛蹄塘组黑色页岩,重点研究应用低温氮气吸附法分析其孔径分布的测试条件,系统探讨了样品质量、脱气温度、升温速率和脱气时间对测试结果的影响,通过进一步优化参数建立了可靠的孔径分布测试方法,并成功用于测定其他页岩样品。结果表明:吸附-脱附等温线呈反C型,属于Brunauer等提出的BDDT等温吸附曲线分类中的V型,滞后环完全闭合,属于IUPAC分类中的H4型,对应狭窄的狭缝型孔隙,说明此类页岩中除了含有峰值孔径主要集中在3.5~4.5 nm的中孔和一定数量的大孔外,还存在大量微孔。研究认为脱气温度是影响测试结果的主要因素。该研究是页岩孔径分布测试方法的一项补充,为我国页岩气的深入研究提供了关键参数支持。     

基于GIPL2模型的青藏高原活动层土壤热状况模拟研究

青藏高原活动层土壤热状况,对深入了解高原活动层的厚度变化特征、下垫面的热力作用以及对气候变化预测均有重要意义。利用GIPL2模型模拟青藏高原多年冻土区不同植被状况下活动层土壤热状况。模拟结果表明：模型在高寒草原（QT06）试验点模拟效果较好,高寒沼泽草甸（QT03）试验点的模拟效果较差,高寒草甸（QT01）、高寒荒漠草原（QT05）和高寒草原化草甸（QT04）试验点的模拟效果介于高寒草原试验点和高寒沼泽草甸试验点之间。QT01、QT03、QT04、QT05和QT06的土壤温度模拟值与观测值相比,均方根误差分别为0.67、1.29、0.73、0.7和0.56℃;相关系数分别为0.99、0.87、0.98、0.98和0.96;平均误差分别为0.37、0.61、0.31、0.45和0.16℃。QT06模拟结果较好,原因在于此点土壤质地变化不大,模型的分层与所取的参数更加接近此点的实际状况。QT03模拟结果较差,可能由于此地区土壤中存在砾石,在导热率参数化方案中没有考虑砾石含量,导致模拟结果偏差较大。总体而言,GIPL2模型对青藏高原活动层土壤热状况的模拟具有一定的优势,是一种模拟多年冻土区活动层土壤热状况较为理想的模型。     

基于支持向量机的喀斯特山区土壤环境质量评价——以贵州北部一茶叶园区为例

以贵州北部一茶叶园区80个表层土壤样品为研究对象,对其Hg、As、Cd、Pb、Cr和Cu含量进行测定,在MATLAB中应用支持向量机构建土壤环境质量评价模型,并与模糊综合评价法和内梅罗综合污染指数法的评价结果对比分析,探究支持向量机模型在喀斯特山区土壤环境质量评价中的适用性,其结果表明:研究区土壤质量Ⅰ类与Ⅱ类样品比例为33∶7,土壤环境质量大多数为I类;支持向量机方法的评价结果与模糊综合评价法和内梅罗综合污染指数法结果的相同率分别达到82.5%和80.0%,并分析结果有差异的样品,发现支持向量机评价结果更符合实际情况,这说明该模型适用于土壤环境质量的评价。      

2-D delineation of individual citrus trees from UAV-based dense photogrammetric surface models

One of the challenges of remote sensing and computer vision lies in the three-dimensional (3-D) reconstruction of individual trees by using automated methods through very high-resolution (VHR) data sets. However, a successful and complete 3-D reconstruction relies on precise delineation of the trees in two dimensions. In this paper, we present an original approach to detect and delineate citrus trees using unmanned aerial vehicles based on photogrammetric digital surface models (DSMs). The symmetry of the citrus trees in a DSM is handled by an orientation-based radial symmetry transform which is computed in a unique way. Next, we propose an efficient strategy to accurately build influence regions of each tree, and then we delineate individual citrus trees through active contours by taking into account the influence region of each canopy. We also present two efficient strategies to filter out erroneously detected canopy regions without having any height thresholds. Experiments are carried out on eight test DSMs composed of different types of citrus orchards with varying densities and canopy sizes. Extensive comparisons to the state-of-the-art approaches reveal that our proposed approach provides superior detection and delineation performances through supporting a nice balance between precision and recall measures.     

Brittleness index predictions from Lower Barnett Shale well-log data applying an optimized data matching algorithm at various sampling densities

The capability of accurately predicting mineralogical brittleness index(BI)from basic suites of well logs is desir-able as it provides a useful indicator of the fracability of tight formations.Measuring mineralogical components in rocks is expensive and time consuming.However,the basic well log curves are not well correlated with BI so correlation-based,machine-learning methods are not able to derive highly accurate BI predictions using such data.A correlation-free,optimized data-matching algorithm is configured to predict BI on a supervised basis from well log and core data available from two published wells in the Lower Barnett Shale Formation(Texas).This transparent open box(TOB)algorithm matches data records by calculating the sum of squared errors be-tween their variables and selecting the best matches as those with the minimum squared errors.It then applies optimizers to adjust weights applied to individual variable errors to minimize the root mean square error(RMSE)between calculated and predicted(BI).The prediction accuracy achieved by TOB using just five well logs(Gr,pb,Ns,Rs,Dt)to predict BI is dependent on the density of data records sampled.At a sampling density of about one sample per 0.5 ft BI is predicted with RMSE～0.056 and R2～0.790.At a sampling density of about one sample per 0.1 ft BI is predicted with RMSE～0.008 and R2～0.995.Adding a stratigraphic height index as an additional(sixth)input variable method improves BI prediction accuracy to RMSE～0.003 and R2～0.999 for the two wells with only 1 record in 10,000 yielding a BI prediction error of＞±0.1.The model has the potential to be applied in an unsupervised basis to predict BI from basic well log data in surrounding wells lacking mineralogical measure-ments but with similar lithofacies and burial histories.The method could also be extended to predict elastic rock properties in and seismic attributes from wells and seismic data to improve the precision of brittleness index and fracability mapping spatially.