对山西地震前兆台网运行工作的思考

文章对省地震局地震前兆台站的建设现状、发展状况及前兆台网室现行的管理、运行模式做了一一介绍。针对此,提出了几点改进建议,对前兆台网的正常运行,提高观测质量、观测数据的利用率有一定的参考价值。     

Toppling and stabilization of the intake slope for the Fengtan Hydropower Station enlargement project, Mid-South China

The intake slope for the Fengtan Hydropower Station enlargement project is composed of thickly bedded sedimentary rock. During excavation of the intake slope and tunnels, toppling was observed in the rock masses of the intake slope. Research was conducted to study the engineering geological conditions and the deformation characteristics of the slope during excavation. The in situ monitoring data and possible causes for toppling were analyzed. A method for analyzing monitoring data was proposed, which can be used to calculate the depth and rotation angle of block toppling. The monitoring results showed that toppling occurred only at a shallow depth, and induced local instability of the slope. Deformation had been controlled and the slope tended to be stable after reinforcement. Through this case study, it can be seen that the stability of the slope and underground openings during and after excavation is variable, especially when the loading conditions and topography are changed. A proper construction sequence is essential, i.e., excavation from the inside toward the free slope surface; excavating the slope above the tunnel after the tunnel lining is in place. This is particularly important for the excavation of multiple tunnels at the slope toe.     

A comparative study of Monte Carlo simple genetic algorithm and noisy genetic algorithm for cost-effective sampling network design under uncertainty

This study evaluates and compares two methodologies, Monte Carlo simple genetic algorithm (MCSGA) and noisy genetic algorithm (NGA), for cost-effective sampling network design in the presence of uncertainties in the hydraulic conductivity (K) field. Both methodologies couple a genetic algorithm (GA) with a numerical flow and transport simulator and a global plume estimator to identify the optimal sampling network for contaminant plume monitoring. The MCSGA approach yields one optimal design each for a large number of realizations generated to represent the uncertain K-field. A composite design is developed on the basis of those potential monitoring wells that are most frequently selected by the individual designs for different K-field realizations. The NGA approach relies on a much smaller sample of K-field realizations and incorporates the average of objective functions associated with all K-field realizations directly into the GA operators, leading to a single optimal design. The efficacy of the MCSGA-based composite design and the NGA-based optimal design is assessed by applying them to 1000 realizations of the K-field and evaluating the relative errors of global mass and higher moments between the plume interpolated from a sampling network and that output by the transport model without any interpolation. For the synthetic application examined in this study, the optimal sampling network obtained using NGA achieves a potential cost savings of 45% while keeping the global mass and higher moment estimation errors comparable to those errors obtained using MCSGA. The results of this study indicate that NGA can be used as a useful surrogate of MCSGA for cost-effective sampling network design under uncertainty. Compared with MCSGA, NGA reduces the optimization runtime by a factor of 6.5.     

Designing a monitoring network for detecting groundwater pollution with stochastic simulation and a cost model

A method is presented to design monitoring networks for detecting groundwater pollution at industrial sites. The goal is to detect the pollution at some distance from the site’s boundary so that it can be cleaned up or hydrologically contained before contaminating groundwater outside the site. It is assumed that pollution may occur anywhere on the site, that transport is by advection only and that no retardation and chemical reactions take place. However, the approach can be easily extended to include designated (and uncertain) source areas, dispersion and reactive transport. The method starts from the premise that it is impossible to detect 100% of all the contaminant plumes with reasonable costs and therefore seeks a balance between the risk of pollution and network density. The design approach takes account of uncertainty in the flow field by simulating realisations of conductivity, groundwater head and associated flow fields, using geostatistical simulation and a groundwater flow model. The realisations are conditioned to conductivity and head observations that may already be present on the site. The result is an ensemble of flow fields that is further analysed using a particle track program. From this the probability of missing a contaminant plume originating anywhere on the terrain can be estimated for a given network. From this probability follows the risk, i.e. the expected costs of an undetected pollution. The total costs of the monitoring strategy are calculated by adding the risk of pollution to the costs of installing and maintaining the monitoring wells and the routinely performed chemical analyses. By repeating this procedure for networks of varying well numbers, the best network is chosen as the one that minimises total cost. The method is illustrated with a simulated example showing the added worth of exploratory wells for characterising hydraulic conductivity of a site.     

展望地震监测台网的发展与应用

随着国民经济的快速发展，我国地震监测台网的发展也日新月异，设备性能、技术系统、台网密度正逐步接近发达国家的水平，同时积累了大量的观测数据。如何利用这些监测资源，更好地为经济建设和社会公共安全服务，是值得研究的重要问题。本文认为提取有用的地震前兆信息、提升地震速报能力、扩展烈度速报功能是地震监测台网为地震预报和地震应急服务的重点；整合台网资源，构筑统一标准、多用途的地震监测网络是建设公共安全服务技术平台的前提；工程、海洋、气象、环保等是地震监测资源的主要服务领域。因此，开发监测资源，加强自主创新，构筑技术平台，拓展服务领域是未来地震监测台网为社会和公共安全服务的重要发展方向。     

抗差拟合推估在基坑支护结构变形监测中的应用

本文提出了利用二次曲面函数和多面函数法构建基坑监测面变形模型的方法，并将稳健估计应用于监测数据处理中。通过实例分析，指出了二次曲面函数法适合无支撑的苦坑监测面位移模型拟合，多面函数法适合有支撑的基坑监测面位移模型拟合。最后，对如何确定多面函数法的中心点个数作了讨论．得出了有益的结论。     

基于RS和GIS的县级土地利用动态监测研究--以河北省万全县为例

本文以两期卫星影像作为主要信息源，并辅以地面调查，通过综合运用地理信息系统和遥感技术，成功获取了河北省万全县土地利用的变化信息。同时还对动态监测的工作流程以及关键技术进行了分析和探讨。     

The use of surface monitoring data for the interpretation of landslide movement patterns

The Tessina landslide is a large, seasonally active slope failure located on the southern slopes of Mt. Teverone, in the Alpago valley of NE Italy, consisting of a complex system that has developed in Tertiary Flysch deposits. The landslide, which first became active in 1960, threatens two villages and is hence subject to detailed monitoring, with high quality data being collected using piezometers, inclinometers, extensometers, and through the use of a highly innovative, automated Electronic Distance Measurement (EDM) system, which surveys the location of a large number of reflector targets once every 6 h. These systems form the basis of a warning system that protects the villages, but they also provide a very valuable insight into the patterns of movement of the landslide.In this paper, analysis is presented of the movement of the landslide, concentrating on the EDM dataset, which provides a remarkable record of surface displacement patterns. It is proposed that four distinct movement patterns can be established, which correspond closely to independently defined morphological assessments of the landslide complex. Any given block of material transitions through the four phases of movement as it progresses down the landslide, with the style of movement being controlled primarily by the groundwater conditions. The analysis is augmented with modelling of the landslide, undertaken using the Itasca FLAC code. The modelling suggests that different landslide patterns are observed for different parts of the landslide, primarily as a result of variations in the groundwater conditions. The model suggests that when a movement event occurs, displacements occur initially at the toe of the landslide, then retrogress upslope.     

Monitoring and simulation of water, heat, and CO2 fluxes in terrestrial ecosystems based on the APEIS-FLUX system

The Integrated Environmental Monitoring (IEM) project, part of the Asia-Pacific Environmental Innovation Strategy (APEIS) project, developed an integrated environmental monitoring system that can be used to detect, monitor, and assess environmental disasters, degradation, and their impacts in the Asia-Pacific region. The system primarily employs data from the moderate resolution imaging spectrometer (MODIS) sensor on the Earth Observation System- (EOS-) Terra/Aqua satellite, as well as those from ground observations at five sites in different ecological systems in China. From the preliminary data analysis on both annual and daily variations of water, heat and CO2 fluxes, we can confirm that this system basically has been working well. The results show that both latent flux and CO2 flux are much greater in the crop field than those in the grassland and the saline desert, whereas the sensible heat flux shows the opposite trend. Different data products from MODIS have very different correspondence, e.g. MODIS-derived land surface temperature has a close correlation with measured ones, but LAI and NPP are quite different from ground measurements, which suggests that the algorithms used to process MODIS data need to be revised by using the local dataset. We are now using the APEIS-FLUX data to develop an integrated model, which can simulate the regional water, heat, and carbon fluxes. Finally, we are expected to use this model to develop more precise high-order MODIS products in Asia-Pacific region.