基于组合权重与灰色关联度分析法的地铁深基坑开挖稳定性评价

伴随着城市的快速发展,地铁深基坑工程越来越多。在开挖过程中如何对其稳定性进行评价,是当前需要重点关注的问题。以成都地铁十七号线凤溪站深基坑支护开挖工程为依托,利用层次分析确定的主观权重与利用熵值法确定的客观权重计算获得组合权重,并与灰色关联度分析法相结合,通过现场数据采集并进行综合评判,客观评价地铁深基坑开挖的稳定性。结果表明,各监测项目对基坑稳定性的重要程度从大到小依次为桩顶水平位移（0.29）、地表沉降（0.24）、建筑物沉降（0.19）、桩顶沉降（0.18）、内支撑轴力（0.10）,基坑稳定性综合评判结果等级为"非常好"。所建立的评价模型可为类似地铁深基坑开挖稳定性评价提供新的方法。     

面向河套区域农业的气象地理信息系统研究

针对河套区域农业气象服务需求,基于GIS技术成果,提出区域农业的气象地理信息系统设计构想,运用WEBGIS技术和B/S结构,完成该气象地理信息系统服务内容的设计,实现对区域农业气象服务的多源气象数据的采集、编辑、存储、分析、可视化查询,为区域农业发展提供多方位的高效信息服务。     

1988-2018年滇池氮磷比的时空演变特征与原因解析

氮、磷浓度是制约湖泊营养状态和生产力水平的重要环境因子,而氮磷化学计量比是湖泊生态系统的主要指标,因此,判识氮磷比变化趋势及其驱动力对湖泊生态恢复具有重要意义.研究基于19882018年连续观测数据,分析了滇池氮磷浓度和氮磷摩尔比(简称氮磷比)的时空分布演变特征;采用多元线性回归模型分别对滇池草海和外海氮磷比驱动效应进行定量解析,筛选出影响湖体氮磷比变化的潜在驱动因子.结果表明:①19882018年滇池氮磷比呈现显著的线性上升趋势,其中草海和外海氮磷比分别上升1.3和0.7 a^-1.②草海和外海分别在2008年和2004年发生了氮磷比上升突变,突变前上升归因于总氮浓度快速增加,突变后则是由于总磷浓度下降较快.③滇池的氮磷浓度变化主要是受流域氮磷输入负荷、跨流域调水、流域氮磷削减、风速和水位的综合影响,但受控因子在不同区域可能存在差异.④气温是滇池氮磷比变化的主要驱动因子,流域人为氮磷输入差异是滇池氮磷比变化的次要驱动因子.     

Optimum size and density of surface grid arrays for retrieving accurate shear-tensile fracturing of microearthquakes

Surface arrays became an important tool for monitoring the induced seismicity in hydraulic fracturing experiments and for assessing the impact of fluid injection on the fracturing process of microearthquakes. The layout of sensors plays a key role in this task because it controls the accuracy of event locations and retrieved seismic moment tensors. We simulate various configurations of grid sensor arrays characterized by a different number of sensors, array span, sensor spacing, depth of sources and various shear/tensile source mechanisms of events. The moment tensor inversion is carried out using synthetically calculated P-wave amplitudes with added random noise. A bias in the solutions is evaluated by errors in the double-couple percentage of inverted moment tensors because the double-couple errors inform us about the sensitivity of the network to detect the shear/tensile fracturing mode of induced microearthquakes. The results show that the accuracy of the double-couple percentage is mostly controlled by the offset-to-depth ratio R defined as the ratio of half of the network size to the event depth. The optimum value of R is in the range of 0.75–1.5 irrespective of the type of the focal mechanism. If 121 (11 × 11) sensors are distributed in a regular grid and recorded data are characterized by a 10% random noise, the double-couple error is less than 6%. This error increases, if R is not optimum or if the number of sensors is reduced. However, even sparse arrays with 49 (7 × 7) or 16 (4 × 4) sensors can yield a reasonable accuracy, provided the surface grid arrays are designed to have an optimum size.     

Coherence algorithm with a high-resolution time–time transform and feature matrix for seismic data

Traditional coherence algorithms are often based on the assumption that seismic traces are stationary and Gaussian. However, seismic traces are actually non-stationary and non-Gaussian. A constant time window and the canonical correlation analysis in traditional coherence algorithms are not optimal for non-stationary seismic traces and cannot describe the similarity between adjacent seismic traces in detail. To overcome this problem, a new coherence algorithm using the high-resolution time–time transform and the feature matrix is designed. The high-resolution time–time transform used to replace the constant time window can produce a frequency-dependent time local series to analyse non-stationary seismic traces. The feature matrix, constructed by the frequency-dependent time local series and the related local gradients, defines a new correlation metric that enhances more details of the geological discontinuities in seismic images than does the canonical correlation analysis. Additionally, the Riemannian metric is introduced for related calculations because the feature matrices are not defined in a Euclidean space but rather in a manifold space. Application to field data illustrates that the proposed method reveals more details of structural and stratigraphic features.     

Laboratory investigations of the role of biofilms on stream-bed surfaces in debris-flow runout

Debris-flow runout is a fascinating process to understand due to its implications for downstream alluvial fans. Based on the propagation-deposition behaviors of the Dongyuege (DYG) debris flow, in Yunnan, the effect of biofilms on channel surfaces on debris-flow runout is investigated in laboratory flumes with two different internal surfaces: surfaces are lined with granite slabs (Model I) and gravel (Model II), respectively. Our results show that biofilms can significantly reduce frictional resistance to flows. They increase flow velocities, slow down the deceleration of the snouts, prolong runout distances, and subsequently extend the areas covered with resulting deposits, thus greatly assisting the propagation of experimental debris flows. Slippery biofilms consisting mainly of diatoms and their extracellular mucus (ECM) reduce the contact friction between the flume-beds and the overlying fluids, and greatly promote the propagation of tested flows. Well-developed biofilms are found on the underwater channel surfaces of the DYG Creek. Acting as lubricating layers, they likely played a key role in the DYG debris-flow runout. Most of the debris transported during the DYG event was deposited on overbanks, and the sediment that caused the disaster was transported to the populated fan region through the stream-bed clad in the thick biofilms. Owing to their impacts on the development and width of the temporary debris dam breach, the stream-bed covered with biofilms became a direct contributor to the debris-flow hazard. Because of the ubiquitous presence of biofilms on mountain stream-bed surfaces, the development of perennial streamflows can be viewed as an indicator of gully susceptibility to debris flows threatening creek fans. The underwater areas of pre-event channel cross-sections should be regarded as slip or low-friction boundaries, and the parts above stream-levels can be viewed as no-slip boundaries. © 2019 John Wiley & Sons, Ltd.     

基于企业微信的宁波市地震应急工作助手的设计与实现

通过分析市县地震部门的地震应急组织机构、主要职能、关键流程,设计了地震应急工作助手的需求方案。并应用ASP.NET MVC、HTML5等开发技术,基于企业微信,开发了包括震情服务、灾情服务、应急服务、工作报告、资料查询、通知公告、通信录等7大功能的地震应急工作助手软件。该软件具有相对机动灵活、成本低、易于推广使用的优势。多次地震应急演练使用表明,软件能在较大程度上提高地震应急工作的规范化程度和处置效率。     

湖泊水体微生物四醚膜脂化合物研究进展

来源于微生物膜脂的甘油二烷基甘油四醚类(GDGTs)化合物是近年来被广泛用于古环境定量重建研究的化合物之一,究其原因在于此类化合物对环境响应敏感,特别是温度与pH值等,据此而建立的一系列GDGTs指标有效定量重建海洋、湖泊、泥炭以及土壤等不同沉积载体的环境信息.目前已在全球范围广泛开展湖泊沉积物GDGTs的研究工作,相继建立的全球以及不同区域尺度的湖泊沉积物GDGTs校正方程,已被用于湖泊古环境的定量重建研究,有效记载古湖泊环境变迁信息.相较之下,基于湖泊水体GDGTs的调查工作则起步较晚,但越来越多的研究显示,不同类型湖泊水体普遍贡献GDGTs,然而究竟此类水生来源GDGTs是否与陆源以及湖泊沉积物GDGTs具有类似的分布,以及他们对环境因素的响应如何,这都为湖泊古温度定量重建研究带来不确定性.基于此,本文总结这10年来湖泊水体GDGTs研究工作的进展,首先阐述湖泊水体不同来源(古菌以及细菌)GDGTs的分布情况,研究发现水体不同层位GDGTs浓度以及各组分之间存在差异,并且水深在不同湖泊对GDGTs浓度以及各组分相对比例的影响存在差异.此外还总结湖泊水体中古菌来源isoGDGTs以及细菌来源brGDGTs的生物来源,并进一步分析环境因素对不同深度水体GDGTs分布的影响,虽然温度依然是影响水体中GDGTs分布的首要因素之一,然而湖泊水深、温度以及水体中溶解氧浓度等因素存在着一定的耦合关系,这些因素往往协同作用于水体GDGTs,因此会为评估环境因素对水体GDGTs的影响带来难度.     

基于实测与模拟的青海湖冰厚时空变化特征

湖冰厚度是湖泊在封冻期的重要物理参数,明晰其时空变化特征对于认识气候变暖背景下的湖冰响应规律具有重要的理论价值和现实意义.基于ERA5 Climate Reanalysis气温数据集、MODIS MOD09GQ数据产品和2019年湖冰钻孔测厚数据及雷达测厚数据,重建2000—2019年青海湖冰厚时间序列并分析其时空变化特征.结果表明:①2019年3月实测青海湖湖冰厚度平均增长速率为0.30 cm/d,高于2月份(0.12 cm/d).基于度日法湖冰生长模型模拟的2018年11月—2019年3月青海湖冰厚平均增长速率为0.34 cm/d,与实际观测数据相比,模拟冰厚误差为±2 cm,但在河流入湖口处和湖区南侧误差较大,且冰厚模拟数值在3月中旬前高估而之后有所低估.②青海湖多年平均冰厚介于32～37 cm,其中2008—2016年湖冰厚度年际变化剧烈,呈现先增大再稳定后减小的趋势.冻结初期湖冰厚度增长迅速,12月和1月湖冰增长速率分别为0.45和0.41 cm/d,2月后冰厚增长速率放缓,2月和3月分别为0.29和0.14 cm/d.③2000—2019年冰厚整体呈现北厚南薄、东厚西薄的空间格局,多年冰厚变化幅度湖区西部较东部稳定,湖冰平均厚度与完全封冻时长及封冻期呈正相关.     

1988-2016年洞庭湖大型底栖动物群落变化及驱动因素分析

洞庭湖是我国第二大淡水湖泊,其水文条件对湖泊湿地生态系统健康的维系发挥着不可替代的作用.近年来,水环境恶化日益威胁湖区水生态系统健康.然而,有关底栖动物水生态健康评价的研究仍然停留在物种群落结构方面,缺乏底栖动物群落功能对水污染响应的研究,尤其在较长时间尺度上.因而,本研究分析了19882016年近30 a来洞庭湖的水质和底栖动物群落数据,探寻底栖动物群落功能对水环境恶化的响应规律.结果表明,洞庭湖水体总氮浓度是威胁底栖动物物种和功能群落变动的主要因素.此外,不断恶化的水环境驱动底栖动物物种和功能群落结构改变,表现为敏感水生昆虫的比例下降,寡毛类、小型软体动物比例的上升,并伴随着体长为1.00~1.99 cm、背扁型、侧扁型、不移动等功能性状类别比例的下降.同时,水环境恶化降低物种丰富度、功能丰富度和劳氏二次熵多样性.基于距离的冗余分析结果显示,水体氮营养盐、重金属离子和有机污染物共同驱动底栖动物物种群落结构的变异,而营养盐类与无/有机污染物决定着其功能群落结构的变异.鉴于洞庭湖水质不断恶化的状况,本研究建议采取一系列措施,包括合理管控湖区周边废水直排入湖、取缔湖区内的非法采砂以及调控枯水季洞庭湖水位等.生物监测和评价方面,建议将底栖动物物种和功能群落一并纳入评价体系,且优先选用物种丰富度、功能丰富度和劳氏二次熵指数评估换水周期较短的大型浅水湖泊水质变化对底栖动物物种和功能多样性的影响.