A study on quality of aquatic environment in Tumen River Area

After the survey of pollution sources, a study on surface water quality assessment and forecast is given by means of grey system method, fuzzy mathematical method and multiple-index method. Based on it, aquatic environment quality features, treatment measures and environmental strategies of the area are proposed. The quality of aquatic environment of 5 rivers in the Tumen River area is studied. The results show that the pollution of surface water is serious; water quality of most rivers is between grade IV and V except the Hunchun River, being higher than grade IV standard; pollution levels of most rivers have been basically controlled except the of Burhatong River, which is deteriorating gradually. Pollutants of the rivers are comparatively regular, mainly are SS, COD, BOD, AR-OH, NH₃-N. The main pollution trades are chemical fibre industry, pulp and paper making industry and mining industry. If the growth rate of gross industrial product is higher than 25 percent under the encouraging-model of regional exploitation, the pollutants’ load will overtake the bearing capacity of aquatic environment. Thus some protection program against pollution must be worked out in order to achieve the harmonious development of economy society and environment. A project from “Studies on Earlier Stage of Regional Development” of the Chinese Academy of Sciences     

雅砻江流域主汛期降水长期预报的一种方法

本文使用天气学方法，从影响雅砻江区域主汛期降水量的长期预报有关因子出发，再运用数理统计方法反复筛选，仅取３个主要因子：西部青藏高原８个站冬春积温，北部冬季极涡面积指数，南部冬季印缅槽平均强度，建立逐步回归预报方程。结果显示：对主汛期６～９月降水量预报拟合准确率为１６／１７即约９４％。回归分析中发现：尽管西太平洋副热带高压对盆地西部降水有很大影响，盛夏且与高原积温有较密切相关，但由放大范围长时段的青藏高原积温，对于雅砻江区域主汛期降水量的影响超过西太平洋副热高压，因而在逐步回归过程中，副高因子仍被剔除．     

武汉区域气象中心数值预报业务并行计算机系统

对武汉区域气象中心并行计算机系统进行了详细地介绍，分析了并行计算机体系结构、网络和存储系统特点；给出了在并行计算机SP上实现数值预报业务并行化的部分结果；对数值预报模式在串、并行编程环境下的结果进行了分析比较。     

临猗5.0级地震前后品质因子值变化特征研究

利用西安数字地震遥测台网记录的数字地震资料，采用P波初动半周期残差法求得1998年7月临猗5．0级地震前后不同路径的Q(品质因子)值变化，发现在地震发生前Q值为87～203，震后Q值为67～164，震前震中区附近出现明显的高Q值异常。结果表明，地震前的高Q值异常可以作为地震预测的一种手段。     

Mapping susceptibility of rainfall-triggered shallow landslides using a probabilistic approach

To prepare a landslide susceptibility map is essential to identify hazardous regions, construct appropriate mitigation facilities, and plan emergency measures for a region prone to landslides triggered by rainfall. The conventional mapping methods require much information about past landslides records and contributing terrace and rainfall. They also rely heavily on the quantity and quality of accessible information and subjectively of the map builder. This paper contributes to a systematic and quantitative assessment of mapping landslide hazards over a region. Geographical Information System is implemented to retrieve relevant parameters from data layers, including the spatial distribution of transient fluid pressures, which is estimated using the TRIGRS program. The factor of safety of each pixel in the study region is calculated analytically. Monte Carlo simulation of random variables is conducted to process the estimation of fluid pressure and factor of safety for multiple times. The failure probability of each pixel is thus estimated. These procedures of mapping landslide potential are demonstrated in a case history. The analysis results reveal a positive correlation between landslide probability and accumulated rainfall. This approach gives simulation results compared to field records. The location and size of actual landslide are well predicted. An explanation for some of the inconsistencies is also provided to emphasize the importance of site information on the accuracy of mapping results.     

An operational multiscale system for hazards prediction, mapping, and response

By definition, a crisis is a situation that requires assistance to be managed. Hence, response to a crisis involves the merging of local and non-local emergency response personnel. In this situation, it is critical that each participant: (1) know the roles and responsibilities of each of the other participants; (2) know the capabilities of each of the participants; and (3) have a common basis for action. For many types of natural disasters, this entails having a common operational picture of the unfolding events, including detailed information on the weather, both current and forecasted, that may impact on either the emergency itself or on response activities. The Consequences Assessment Tool Set (CATS) is a comprehensive package of hazard prediction models and casualty and damage assessment tools that provides a linkage between a modeled or observed effect and the attendant consequences for populations, infrastructure, and resources, and, hence, provides the common operational picture for emergency response. The Operational Multiscale Environment model with Grid Adaptivity (OMEGA) is an atmospheric simulation system that links the latest methods in computational fluid dynamics and high-resolution gridding technologies with numerical weather prediction to provide specific weather analysis and forecast capability that can be merged into the geographic information system framework of CATS. This paper documents the problem of emergency response as an end-to-end system and presents the integrated CATS–OMEGA system as a prototype of such a system that has been used successfully in a number of different situations.     

Quantitative sinkhole hazard assessment. A case study from the Ebro Valley evaporite alluvial karst (NE Spain)

Quantitative sinkhole hazard assessments in karst areas allow calculation of the potential sinkhole risk and the performance of cost-benefit analyses. These estimations are of practical interest for planning, engineering, and insurance purposes. The sinkhole hazard assessments should include two components: the probability of occurrence of sinkholes (sinkholes/km² year) and the severity of the sinkholes, which mainly refers to the subsidence mechanisms (progressive passive bending or catastrophic collapse) and the size of the sinkholes at the time of formation; a critical engineering design parameter. This requires the compilation of an exhaustive database on recent sinkholes, including information on the: (1) location, (2) chronology (precise date or age range), (3) size, and (4) subsidence mechanisms and rate. This work presents a hazard assessment from an alluvial evaporite karst area (0.81 km²) located in the periphery of the city of Zaragoza (Ebro River valley, NE Spain). Five sinkholes and four locations with features attributable to karstic subsidence where identified in an initial investigation phase providing a preliminary probability of occurrence of 0.14 sinkholes/km² year (11.34% in annual probability). A trenching program conducted in a subsequent investigation phase allowed us to rule out the four probable sinkholes, reducing the probability of occurrence to 0.079 sinkholes/km² year (6.4% in annual probability). The information on the severity indicates that collapse sinkholes 10–15 m in diameter may occur in the area. A detailed study of the deposits and deformational structures exposed by trenching in one of the sinkholes allowed us to infer a modern collapse sinkhole approximately 12 m in diameter and with a vertical throw of 8 m. This collapse structure is superimposed on a subsidence sinkhole around 80 m across that records at least 1.7 m of synsedimentary subsidence. Trenching, in combination with dating techniques, is proposed as a useful methodology to elucidate the origin of depressions with uncertain diagnosis and to gather practical information with predictive utility about particular sinkholes in alluvial karst settings: precise location, subsidence mechanisms and magnitude, and timing and rate of the subsidence episodes.     

TBM在不良地质洞条件下的施工技术

TBM掘进机以其快速、高效、安全、优质等优点越来越广泛地被应用于隧洞开挖施工中,尤其更适用于深埋超长隧洞,然而在不良地质洞段中TBM掘进缓慢,甚至有卡刀可能,反而不如钻爆法灵活,这就需要根据围岩性状采取特殊技术处理措施,辅以监控量测手段对支护方案进行验证、调整支护措施、修正设计参数等。结合辽宁大伙房输水隧洞工程,总结了在不良地质洞条件下的超前地质预报方法、不良地质段处理措施以及围岩变形监测方法。     

PSO-RBFNN模型及其在岩土工程非线性时间序列预测中的应用

岩土工程受力变形演化是一个典型的非线性问题,其演化的高度非线性和复杂性,很难用简单的力学、数学模型描述,但可用粒子群优化径向基神经网络对岩土工程应力、位移非线性时间序列进行动态实时预测。网络径向基层的单元数通过均值聚类法确定后,所有其它参数：中心位置、形状参数、网络权值,均通过粒子群优化算法在全局空间优化确定。工程实例应用表明,该模型预测结果准确、精度高,有良好的应用前景。