地壳脆塑性转化带非稳态流变与震后松弛变形机制

大陆浅源地震密集分布层称为地震层,该深度处于石英脆塑性转化带,其变形除受温度控制外,地震周期各阶段变形随应变速率和应力发生变化,从间震期的稳态蠕变转化为同震破裂和震后松弛阶段非稳态蠕变。与间震期长期蠕变相关的野外塑性变形和稳态流变实验研究非常多,而与震后松弛相关的地壳深部脆塑性转化和非稳态蠕变研究非常有限,更缺少非稳态流变的本构方程。震后松弛阶段的断层滑动研究和基于GPS观测数据反演地壳形变研究都依赖于非稳态蠕变实验数据及其流变模型。本文介绍了野外断层脆塑性转化带非稳态流变和高温高压非稳态流变实验研究进展,分析震后松弛阶段断层脆塑性转化带的变形特征与变形模式,讨论了非稳态流变与脆塑性转化带强度定量化研究中存在的问题。     

Mapping degraded grassland on the Eastern Tibetan Plateau with multi-temporal Landsat 8 data — where do the severely degraded areas occur?

The Tibetan Plateau in Western China is the world’s largest alpine landscape, sheltering a rich diversity of native flora and fauna. In the past few decades, the Tibetan Plateau was found to suffer from grassland degradation processes. Grassland degradation is assumed to not only endanger biodiversity but also to increase the risk for natural hazards in other parts of the country which are ecologically and hydrologically connected to the area. However, the mechanisms behind the degradation processes remain poorly understood due to scarce baseline data and insufficient scientific research.We argue that remote sensing data can help to better understand degradation processes and patterns by: (1) identifying the distribution of severely degraded areas and (2) comparing the patterns of key spatial attributes of the identified areas (altitude above sea level, aspect, slope, administrative districts) with existing theories on degradation drivers. Therefore, we applied four Landsat 8 images covering large portions of the three counties Jigzhi, Baima and Darlag in the Eastern Tibetan Plateau. The dates of the Landsat scenes were selected to cover differing phenological stages of the ecosystem. Reference data were collected with a remotely piloted aircraft and a standard consumer RGB camera. To exploit the phenological information in the Landsat data as well as deal with the problem of cloud cover in multiple images, we developed a straightforward PCA-based procedure to merge the Landsat scenes. The merged Landsat data served as input to a supervised support vector machine classification which was validated with an iterative bootstrap procedure and an additional independent validation set. The considered classes were “high-cover grassland”, “grassland (including several stages of grassland vitality)”, “(severely) degraded grassland”, “green shrubland”, “grey shrubland”, “urban areas” and “water bodies”. Kappa accuracies ranged between 0.84 and 0.93 in the iterative procedure, while the independent validation led to a kappa accuracy of 0.76. Mean producer’s and user’s accuracies for all classes were higher than 80%, and confusion mainly occurred between the two shrubland classes and between the three grassland classes.Analysis of the slope, aspect and altitude values of the vegetation classes revealed that the degraded areas mostly occurred at the higher altitudes of the study area (4300–4600 m), with no strong connection to any specific slope or aspect. High-cover grassland was mostly located on sunny slopes at lower altitudes (less than 4300 m), while shrubland preferred shady, relatively steep slopes across all altitudes. These observations proved to be stable across the examined counties, while the proportions of land-cover classes differed between the examined regions. Most counties showed 5–7% severely degraded land cover. Darlag, the county located at the edge of the permafrost zone, and featuring the highest average altitude and lowest annual temperature and precipitation, was found to suffer from larger areas of severe degradation (14%).Therefore, our findings support a strong connection between degradation patterns and climatic as well as altitudinal gradients, with an increased degradation risk for high altitude areas and areas in colder and drier climatic zones. This is relevant information for pastoral management to avoid further degradation of high altitude pastures.     

京津冀及周边地区冬季能见度与PM2.5浓度和环境湿度的多元回归分析

2013年至今,中国冬季与雾霾相伴的低能见度事件频发,京津冀及周边地区尤为严重。PM_2.5浓度与环境湿度是导致低能见度的最关键影响因素。为了深入研究PM_2.5浓度与环境湿度对大气能见度的影响,利用2017年1月京津冀及周边地区MICAPS气象数据与PM_2.5观测数据,运用天气学诊断分析方法讨论了不同相对湿度下PM_2.5浓度、环境湿度对冬季能见度变化的相对贡献,按照地理环境与污染程度差异将京津冀及周边地区划分为北京-天津地区与河北-山东地区,建立了PM_2.5浓度与环境湿度（由露点温度、温度代表）对能见度的多元回归方程,并对2015、2016、2018、2019年冬季能见度进行了回算检验。结果显示:相对湿度低于70%、PM_2.5浓度低于75 μg/m3时,北京-天津地区与河北-山东地区能见度多高于10 km,PM_2.5浓度升高是此时能见度迅速降低的主导因素;相对湿度从70%上升至85%和PM_2.5浓度从75 μg/m3升高200 μg/m3的共同作用导致了能见度降低到10 km至5 km;能见度进一步从5 km下降至2 km则更多依赖于相对湿度进一步从85%升高至95%,PM_2.5浓度与此时能见度相关减弱;能见度降低至2 km甚至更低主要是由于水汽近饱和状态下（相对湿度95%以上）的雾滴消光引起,与PM_2.5浓度的变化关系不大。与不分组直接拟合相比,以相对湿度85%为界线,分别拟合能见度能够很大程度优化多元回归模型,相对湿度高于85%时能见度拟合值的均方根误差从9.2和5.2 km下降至0.5和0.7 km,5 km以下拟合能见度的误差大幅度减小。按相对湿度85%将数据分组所得的拟合方程对2015、2016、2018、2019年1月能见度估算结果较好,观测值与拟合值相关系数均高于0.91,为雾-霾数值预报系统提供了新的能见度参数化算法。      

基于MonoRTM模型的微波辐射计反演方法研究

基于辐射传输模型MonoRTM计算天空亮温度,使用多元线性统计回归方法和BP神经网络方法分别对大气温度和水汽密度廓线进行了反演,检验并分析了两种方法的反演精度.结果表明,多元线性回归方法反演的温度偏差总体不大于6K,反演的水汽密度偏差小于4 g/m3;神经网络方法反演的温度偏差小于2K,反演的水汽密度误差总体不大于2 g/m3.与探空数据的对比表明,对于大气温度和水汽密度反演,BP神经网络方法的反演结果都要比多元线性回归方法的反演结果更接近探空资料值.     

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????????????????????Burgers????????????????????????α? ??????????:??Burgers????????????????????????????????????????????????????????????????????????????? ???????????Burgers??????????????????Maxwell???Kelvin??????????????????α?????Э??????     

圈闭地形内斜坡破坏的多期性和规律性

本文以黄河上游某拟建水电站坝址场地为例,论证了圈闭地形内斜坡破坏的多期性和规律性问题。在充分的野外调查和室内研究资料的基础上,将区内的斜坡破坏分为两期,即第一期为已经失稳的老滑坡群;第二期为发育在第一期滑坡群圈闭状破裂壁之后的正处于蠕动和破坏阶段的变形坡体,进而将第一期的滑坡分为两个强度次序。同时,还揭示了圈闭地形内斜坡破坏的规律性,即随着期和序次的增高,斜坡破坏面积增大,滑坡个数增多,规模减小,强度降低,滑距变短,滑体破碎程度变弱。最后指出,上述多期性和规律性应具有普遍性意义。     

Assessing cause and effect of multiple stressors on marine systems

An operational framework is developed to serve as a guideline for investigating causal relationships between environmental stressors and effects on marine biota. Because of the complexity and variability of many marine systems, multiple lines of evidence are needed to understand relationships between stressors and effects on marine resources. Within this framework, a weight of evidence approach based on multiple lines of evidence are developed and applied in a sequential manner by (1) characterizing the study system which involves determining if target biota are impaired, assessment of food and habitat availability, and measuring contaminant levels in the environment, (2) assessing direct effects of contaminant exposure on target biota using biomarkers and assessing indirect effects of exposure using suites of bioindicators, and (3) applying standard causal criteria based on epidemiological principles and diagnostic health profiling techniques to assess potential causes. Use of multiple lines of evidence should also reduce the risk of false positives (Type I error or falsely concluding that there is a causal relationship when there is none) and false negatives (Type II error or falsely concluding there is not a causal relationship when there actually is). Understanding causal relationships and the mechanistic processes between environmental stressors and effects on biota is important in the effective management and restoration of impaired marine ecosystems.     

Volcanic risk ranking for Auckland, New Zealand. I: Methodology and hazard investigation

Volcanic eruptions typically produce a number of hazards, and many regions are at risk from more than one volcano or volcanic field. So that detailed risk assessments can be carried out, it is necessary to rank potential volcanic hazards and events in terms of risk. As it is often difficult to make accurate predictions regarding the characteristics of future eruptions, a method for ranking hazards and events has been developed that does not rely on precise values. Risk is calculated individually for each hazard from each source as the product of likelihood, extent and effect, based on the parameters order of magnitude. So that multiple events and outcomes can be considered, risk is further multiplied by the relative probability of the event occurring (probability_e) and the relative importance of the outcome (importance_o). By adding the values obtained, total risk is calculated and a ranking can be carried out.This method was used to rank volcanic hazards and events that may impact the Auckland Region, New Zealand. Auckland is at risk from the Auckland volcanic field, Okataina volcanic centre, Taupo volcano, Tuhua volcano, Tongariro volcanic centre, and Mt. Taranaki volcano. Relative probabilities were determined for each event, with the highest given to Mt. Taranaki. Hazards considered were, for local events: tephra fall, scoria fall and ballistic impacts, lava flow, base surge and associated shock waves, tsunami, volcanic gases and acid rain, earthquakes and ground deformation, mudflows and mudfills, lightning and flooding; and for distal events: tephra fall, pyroclastic flows, poisonous gases and acid rain, mudflows and mudfills, climate variations and earthquakes. Hazards from each source were assigned values for likelihood, with the largest for tephra fall from all sources, earthquakes and ground deformation, lava flows, scoria fall and base surge for an Auckland eruption on land, and earthquakes and ground deformation from an Auckland eruption in the ocean. The largest values for extent were for tephra fall and climate variation from each of the distal centres. However, these parameters do not give a true indication of risk. In a companion paper the effect of each hazard is fully investigated and the risk ranking completed.     

Multiple solutions in preliminary orbit determination from three observations

Charlier’s theory (1910) provides a geometric interpretation of the occurrence of multiple solutions in Laplace’s method of preliminary orbit determination, assuming geocentric observations. We introduce a generalization of this theory allowing to take into account topocentric observations, that is observations made from the surface of the rotating Earth. The generalized theory works for both Laplace’s and Gauss’ methods. We also provide a geometric definition of a curve that generalizes Charlier’s limiting curve, separating regions with a different number of solutions. The results are generically different from Charlier’s: they may change according to the value of a parameter that depends on the observations.     

利用激发极化驰豫时间谱确定渗透率的实验研究

激发极化驰豫时间是孔隙大小的函数,采用奇异值分解方法对激发极化衰减曲线进行多指数反演,得到光滑的驰豫时间谱,该谱呈现多峰特性.实验结果表明,溶质对该谱的影响主要是由于溶质离子的扩散系数不同所致.对于同一块岩心,衰减谱随扩散系数的增大而向小驰豫时间方向移动.结合岩心地层因素F,研究了激发极化驰豫时间几何平均值Tg与岩石的渗透率K的关系,结果表明,logK和log(T1/2g/F)、log(Tg/F)呈现良好的线性关系.