隧道工程地震易损性分析研究综述与展望

易损性分析是隧道工程领域防震减灾研究的重要方法。首先,详细综述了国内外隧道地震易损性研究历史与现状;其次,归纳了国内外隧道地震易损性分析主要方法,并总结了各种方法的实际适用性;接着,提出了隧道地震易损性评估步骤,并且讨论了以数值模拟为主要手段的理论易损性曲线建立中的3个关键内容:(1)输入参数确定;(2)破坏状态分级;(3)相关不确定性参数计算;最后,指出该领域一些亟待解决的问题和未来研究发展的方向。结果表明:隧道地震易损性分析能通过考虑相关不确定性因素,反映了隧道在地震荷载作用下的性能,有利于未来的风险评估和损失估算,对基于性能的隧道抗震设计的发展具有重要意义。     

Devonian integrative stratigraphy and timescale of China

The Global Boundary Stratotype Sections and Points(GSSPs) for the bases of all seven international Devonian stages have been formally defined and ratified by IUGS till 1996, and nowadays, the main tasks for Devonian stratigraphers include further subdivision of these standard stages, strictly constrained absolute ages for the boundaries, and precise neritic-pelagic and marine-terrestrial correlations using multidisciplinary stratigraphy methods. Establishment of high-resolution Devonian integrative stratigraphy framework and timescale of China would play an important role in improving regional and international correlation, facilitating the recognition of important stratigraphic levels in different paleogeographic settings, and understanding the evolution pattern of biota, paleoclimate and paleoenvironment during this critical interval. Based on well-studied bio-and chronostratigraphy of Devonian in South China and adjacent areas, in combination with recent achievements in carbon isotope stratigraphy, event stratigraphy and radioactive isotope ages, this paper briefly summarize the research history and current status of Devonian chronostratigraphy of China, and for the first time introduce Devonian integrative stratigraphy framework of China.Up to date, few studies have been conducted on the astronomical cyclostratigraphy and high-resolution radioactive isotope dating in Devonian of China, which should be our main focuses in the near future.     

河北广平地震台数字电扰动异常分析

自2018年1月11日,河北广平地震台数字电扰动仪NS、EW测道每日北京时间18时至次日06时出现规律性高值变化。通过观测系统检测、测区环境调查、现场实验分析、周边台站观测对比、其他台干扰形态分析及震例总结等手段,并对各种可能的影响因素进行分析论证,综合分析认为,该变化为干扰的可能性较大,非地震前异常。     

Spatio-temporal differentiation of spring phenology in China driven by temperatures and photoperiod from 1979 to 2018

Large amounts of data accumulated in ecology and related environmental sciences arouses urgent need to explore useful patterns and information in it. Here we propose coclustering-based methods and a temperatures-photoperiod driven phenological model to explore spatio-temporal differentiation in long-term spring phenology in China. First, we created the first bloom date(FBD) dataset in China from 1979 to 2018 using the extended spring indices and China Meteorological Forcing Dataset. Then we analyzed the dataset using Bregman block average co-clustering algorithm with I-divergence(BBAC_I) and kmeans algorithm. Such analysis delineated the spatially-continuous phenoregions in China for the first time. Results showed three spatial patterns of FBD in China and their temporal dynamics for 40 years(1979–2018). More specifically, overall late spring onsets occur in 1979–1996, in which areas located in Jiangxi, northern Xinjiang and middle Inner Mongolia experienced constant changing spring onsets. Overall increasingly earlier spring onsets occur in 1997–2012, in which areas located in Fujian,Hunan and eastern Heilongjiang experienced the most variable spring onsets. Stable early spring onsets over China occur after 2012. Results also showed 15 temporal patterns of spring phenology over the study period and their spatial delineation in China.More specifically, most areas in China have the same FBD category for 40 years while northern Guizhou, Hunan and southern Hubei have the same category in 1979–1997 and then fluctuate between different categories. Finally, our results have certain directive significance on the design of existing observational sites in Chinese Phenological Network.     

基于相对风险模型的土地利用变化生态风险定量评价——以石羊河流域为例

土地利用是否合理是推进国民经济发展的关键,也是生态环境变化的风向标。通过理论研究和实地调研,构建了土地利用生态风险定量评价体系,借助相对风险模型（RRM）对石羊河流域的生态风险及其影响因素进行研究。结果表明：（1）在划分的3个评价单元中,中部绿洲生态保护区在土地利用中面临的生态风险最大,北部盆地防沙治沙区次之,南部山地水源涵养区生态风险最小;（2）在3大风险单元的6类不同风险源中,工程建设对石羊河流域的生态风险影响最大,其次是作物种植和畜牧养殖,且在自然环境相对较好的区域表现得尤为明显。     

Groundwater depth prediction in a shallow aquifer in north China by a quantile regression model

There is a close relationship between groundwater level in a shallow aquifer and the surface ecological environment; hence, it is important to accurately simulate and predict the groundwater level in eco-environmental construction projects. The multiple linear regression (MLR) model is one of the most useful methods to predict groundwater level (depth); however, the predicted values by this model only reflect the mean distribution of the observations and cannot effectively fit the extreme distribution data (outliers). The study reported here builds a prediction model of groundwater-depth dynamics in a shallow aquifer using the quantile regression (QR) method on the basis of the observed data of groundwater depth and related factors. The proposed approach was applied to five sites in Tianjin city, north China, and the groundwater depth was calculated in different quantiles, from which the optimal quantile was screened out according to the box plot method and compared to the values predicted by the MLR model. The results showed that the related factors in the five sites did not follow the standard normal distribution and that there were outliers in the precipitation and last-month (initial state) groundwater-depth factors because the basic assumptions of the MLR model could not be achieved, thereby causing errors. Nevertheless, these conditions had no effect on the QR model, as it could more effectively describe the distribution of original data and had a higher precision in fitting the outliers.     

A comparative study of landslide susceptibility mapping using weight of evidence,logistic regression and support vector machine and evaluated by SBAS-InSAR monitoring: Zhouqu to Wudu segment in Bailong River Basin,China

The determining of landslide-prone areas in mountainous terrain is essential for land planning and hazard mitigation. In this paper, a comparative study using three statistical models including weight of evidence model (WoE), logistic regression model (LR) and support vector machine method (SVM) was undertaken in the Zhouqu to Wudu segment in the Bailong River Basin, Southern Gansu, China. Six conditionally independent environmental factors, elevation, slope, aspect, distance from fault, lithology and settlement density, were selected as the explanatory variables that may contribute to landslide occurrence based on principal component analysis (PCA) and Chi-square test. The relation between landslide distributions and these variables was analyzed using the three models and the results then used to calculate the landslide susceptibility (LS). The performance of the models was then evaluated using both the highly accurate deformation signals produced by using the Small Baseline Subset Interferometric Synthetic Aperture Radar technique and Receiver Operating Characteristic (ROC) curve. Results show more deformation points in areas with high and very high LS levels, and also more stable points in areas with low and very low LS levels for the SVM model. In addition, the SVM has larger area under the ROC curve. It indicates that the SVM has better prediction accuracy and classified ability. For the interpretability, the WoE derives the class of factors that most contributed to landsliding in the study area, and the LR reveals that factors including elevation, settlement density and distance from fault played major roles in landslide occurrence and distribution, whereas the SVM cannot provide relative weights for the variables. The outperformed SVM could be employed to determine potential landslide zones in the study area. Outcome of this research would provide preliminary basis for general land planning such as choosing new urban areas and infrastructure construction in the future, as well as for landslide hazard mitigation in Bailong River Basin.     

Shifting Correlation Between Earthquakes and Electromagnetic Signals: A Case Study of the 2013 Minxian–Zhangxian ML 6.5 (MW 6.1) Earthquake in Gansu,China

The shifting correlation method (SCM) is proposed for statistical analysis of the correlation between earthquake sequences and electromagnetic signal sequences. In this method, the two different sequences were treated in units of 1 day. With the earthquake sequences fixed, the electromagnetic sequences were continuously shifted on the time axis, and the linear correlation coefficients between the two were calculated. In this way, the frequency and temporal distribution characteristics of potential seismic electromagnetic signals in the pre, co, and post-seismic stages were analyzed. In the work discussed in this paper, we first verified the effectiveness of the SCM and found it could accurately identify indistinct related signals by use of sufficient samples of synthetic data. Then, as a case study, the method was used for analysis of electromagnetic monitoring data from the Minxian–Zhangxian M_L 6.5 (M_W 6.1) earthquake. The results showed: (1) there seems to be a strong correlation between earthquakes and electromagnetic signals at different frequency in the pre, co, and post-seismic stages, with correlation coefficients in the range 0.4–0.7. The correlation was positive and negative before and after the earthquakes, respectively. (2) The electromagnetic signals related to the earthquakes might appear 23 days before and last for 10 days after the shocks. (3) To some extent, the occurrence time and frequency band of seismic electromagnetic signals are different at different stations. We inferred that the differences were related to resistivity, active tectonics, and seismogenic structure.     

Retrieval of super‐virtual refraction by cross‐correlation

Topography and severe variations of near‐surface layers lead to travel‐time perturbations for the events in seismic exploration. Usually, these perturbations could be estimated and eliminated by refraction technology. The virtual refraction method is a relatively new technique for retrieval of refraction information from seismic records contaminated by noise. Based on the virtual refraction, this paper proposes super‐virtual refraction interferometry by cross‐correlation to retrieve refraction wavefields by summing the cross‐correlation of raw refraction wavefields and virtual refraction wavefields over all receivers located outside the retrieved source and receiver pair. This method can enhance refraction signal gradually as the source–receiver offset decreases. For further enhancement of refracted waves, a scheme of hybrid virtual refraction wavefields is applied by stacking of correlation‐type and convolution‐type super‐virtual refractions. Our new method does not need any information about the near‐surface velocity model, which can solve the problem of directly unmeasured virtual refraction energy from the virtual source at the surface, and extend the acquisition aperture to its maximum extent in raw seismic records. It can also reduce random noise influence in raw seismic records effectively and improve refracted waves’ signal‐to‐noise ratio by a factor proportional to the square root of the number of receivers positioned at stationary‐phase points, based on the improvement of virtual refraction's signal‐to‐noise ratio. Using results from synthetic and field data, we show that our new method is effective to retrieve refraction information from raw seismic records and improve the accuracy of first‐arrival picks.     

卫星红外遥感技术在我国环保领域中的应用与发展分析

本文较为系统地分析了卫星红外遥感技术在我国秸秆焚烧、沙尘、气溶胶、颗粒物、灰霾等大气环境遥感监测,水华、水质参数、水表温度、热污染、核电厂温排水等水环境遥感监测,以及土壤含水量、地表温度、干旱、城市热岛效应等生态环境遥感监测的应用。同时,指出目前国产卫星红外载荷业务化应用程度不高、辐射定标能力不足、应用反演算法原创性不强、地面观测和试验验证能力不足等问题;并提出需大力发展国产红外传感器、提高辐射定标能力、发展国内原创监测算法、建设大型环保应用综合试验场等建议,以促进红外遥感技术在环境保护领域的应用和发展。