中国锂资源安全评估与预警

锂是中国重要的战略性矿产资源,在锂资源需求快速增加、进口依赖严重的背景下,对中国锂资源安全进行评估与预警具有必要性和紧迫性。构建了以资源禀赋、进口安全、市场风险和地缘政治为一级指标的中国锂资源安全评估指标体系,利用常权和变权模型对2009—2021年中国锂资源安全状况进行了评估,采用ARIMA-BP组合模型对2022—2035年中国锂资源安全进行了预警。研究发现,①进口依赖度、进口集中度和运输通道风险对锂资源安全的影响最大;②2009—2021年中国锂资源安全等级由黄色—基本安全等级波动下降至橙色—不安全等级,资源禀赋和进口安全是导致锂资源安全等级较低的主要原因;③2022—2035年中国锂资源安全评分总体呈下降趋势,除2026年处于黄色—基本安全等级外,其余年份均处于橙色—不安全等级。     

Expected loss‐based alarm threshold set for earthquake early warning systems

Earthquake early warning systems (EEWS) seem to have potential as tools for real‐time seismic risk management and mitigation. In fact, although the evacuation of buildings requires warning time not available in many urbanized areas threatened by seismic hazard, they may still be used for the real‐time protection of critical facilities using automatic systems in order to reduce the losses subsequent to a catastrophic event. This is possible due to the real‐time seismology, which consists of methods and procedures for the rapid estimation of earthquake features, as magnitude and location, based on measurements made on the first seconds of the P‐waves. An earthquake engineering application of earthquake early warning (EEW) may be intended as a system able to issue the alarm, if some recorded parameter exceeds a given threshold, to activate risk mitigation actions before the quake strikes at a site of interest. Feasibility analysis and design of such EEWS require the assessment of the expected loss reduction due to the security action and set of the alarm threshold. In this paper a procedure to carry out these tasks in the performance‐based earthquake engineering probabilistic framework is proposed. A merely illustrative example refers to a simple structure assumed to be a classroom. Structural damage and non‐structural collapses are considered; the security action is to shelter occupants below the desks. The cost due to a false alarm is assumed to be related to the interruption of didactic activities. Results show how the comparison of the expected losses, for the alarm‐issuance and non‐issuance cases, allows setting the alarm threshold on a quantitative and consistent basis, and how it may be a tool for the design of engineering applications of EEW. Copyright © 2007 John Wiley & Sons, Ltd.     

滇西实验场地震中短临动态跟踪综合预测方案及其实践运用

对滇西实验场1992年以来地下流体前兆观测资料进行分析研究,选取应震效果通过R信度检验（对应MS≥5.0级地震）的8条单项前兆指标。综合考虑单项前兆指标虚报率和漏报率对指标信度的影响,对单项前兆指标利用数学模型进行综合处理,减少了虚报和漏报的次数,预测效果明显提高。利用分级预警模式分别建立了中期（T≤6个月）和短临（T≤3个月）预测模型。综合预测方案还提供了地点判定原则和震级估算原则。最终提供地震短临预测三要素。运用本综合预测方案对2011年腾冲5级双震、2013年洱源5级双震和德钦两次5级地震作用了较为成功的短临预测。     

Effective typhoon characteristics and their effects on hourly reservoir inflow forecasting

This paper describes the identification of effective typhoon characteristics and the development of a new type of hourly reservoir inflow forecasting model with the effective typhoon characteristics. Firstly, a comparison of support vector machines (SVMs), which is a novel kind of neural networks (NNs), and back-propagation networks (BPNs) is made to select an appropriate NN-based model. The results show that SVM-based models are more appropriate than BPN-based models because of their higher accuracy and much higher efficiency. In addition, effective typhoon characteristics for improving forecasting performance are identified from all the collected typhoon information. Then the effective typhoon characteristics (the position of the typhoon and the distance between the typhoon center and the reservoir) are added to the proposed SVM-based models. Next, a performance comparison of models with and without effective typhoon characteristics is conducted to clearly highlight the effects of effective typhoon characteristics on hourly reservoir inflow forecasting. To reach a just conclusion, the performance is evaluated by cross validation, and the improvement in performance due to the addition of effective typhoon characteristics is tested by paired comparison t-tests at the 5% significance level. The results confirm that effective typhoon characteristics do improve the forecasting performance and the improvement increases with increasing lead-time, especially when the rainfall data are not available. For four- to six-hour ahead forecasts, the improvement due to the addition of effective typhoon characteristics increases from 3% to 18% and from 10% to 113% for Categories I (rainfall data are available) and II (rainfall data are not available), respectively. In conclusion, effective typhoon characteristics are recommended as key inputs for reservoir inflow forecasting during typhoons. The proposed SVM-based models with effective typhoon characteristics are expected to provide more accurate forecasts than BPN-based models. The proposed modeling technique is also expected to be useful to support reservoir operation systems and other disaster warning systems.     

M TSU : Recovering Seismic Moments from Tsunameter Records

We define a new magnitude scale, M_TSU, allowing the quantification of the seismic moment M₀ of an earthquake based on recordings of its tsunami in the far field by ocean-bottom pressure sensors (``tsunameters') deployed in ocean basins, far from continental or island shores which are known to affect profoundly and in a nonlinear fashion the amplitude of the tsunami wave. The formula for M_TSU, M_TSU = log₁₀ M₀ − 20 = log₁₀ X (ω) + C_D^TSU + C_S^TSU + C₀, where X (ω) is the spectral amplitude of the tsunami, C_D^TSU a distance correction and C_S^TSU a source correction, is directly adapted from the mantle magnitude M_m introduced for seismic surface waves by Okal and Talandier. Like M_m, its corrections are fully justified theoretically based on the representation of a tsunami wave as a branch of the Earth's normal modes. Even the locking constant C₀, which may depend on the nature of the recording (surface amplitude of the tsunami or overpressure at the ocean floor) and its units, is predicted theoretically. M_TSU combines the power of a theoretically developed algorithm, with the robustness of a magnitude measurement that does not take into account such parameters as focal geometry and exact depth, which may not be available under operational conditions in the framework of tsunami warning. We verify the performance of the concept on simulations of the great 1946 Aleutian tsunami at two virtual gauges, and then apply the algorithm to 24 records of 7 tsunamis at DART tsunameters during the years 1994–2003. We find that M_TSU generally recovers the seismic moment M₀ within 0.2 logarithmic units, even under unfavorable conditions such as excessive focal depth and refraction of the tsunami wave around continental masses. Finally, we apply the algorithm to the JASON satellite trace obtained over the Bay of Bengal during the 2004 Sumatra tsunami, after transforming the trace into a time series through a simple ad hoc procedure. Results are surprisingly good, with most estimates of the moment being over 10²⁹ dyn-cm, and thus identifying the source as an exceptionally large earthquake.     

新疆旅游资源的类型、等级及空间分布特征

在全面掌握新疆旅游资源的实查资料基础上,对全疆旅游资源做系统分类与定量评价,总结其类型、等级和空间分布特征,并从新疆地理环境变迁和多民族、多文化的社会环境两方面分析新疆高品质旅游资源的成因。结果表明:新疆旅游资源类型多样,与全国相比,主类、亚类齐全,基本类型占66.5%;八大类中建筑与设施和地文景观的种类较丰富;建筑与设施类景点最多,水域风光和生物景观次之;新疆旅游资源等级较高,优良级占43.6%,整体为中间大两头小的谷仓型结构;高等级集中于凸峰、观光游憩湖区、林地、草地、野生动物栖息地、废城与聚落地、石窟、边境口岸、特色街巷、传统手工产品与制品、民间演艺等类;空间分布呈现为三带两环状和六点状集聚特征,这与新疆地貌格局和高品质景点的聚群作用有关;新疆自然旅游资源是整个地理环境演变过程的产物;而多民族、多文化的社会环境是人文类的主要成因。     

梧州市森林火险气象预报

使用１９８０－１９９１年森林火灾及相应的气象资料，分析了森林火灾与有关气象要素的相关性。在此基础上，计算了森林火险天气预报指标，建立了预报模式，开展了森林火险天气等级预报。经试用效果较好。     

人工神经网络方法在鹤壁汛期降水预报中的应用

在用经验统计方法和降水判别函数进行24h和12h晴雨预报的基础上，再用BP人工神经网络建立降水量级预报模型。经2003年汛期试用，预报准确率高于上级指导预报准确率，12h预报准确率高于24h预报准确率。     

崇左市预警信号发布现状及探讨

统计2008-2013年以来崇左市下辖江州区、扶绥县、天等县、大新县、宁明县、龙州县、凭祥市七县（市、区）,几种常用的气象灾害预警信号发布现状以及实际工作中遇到的问题展开谈论,探讨预警信号发布工作面临的新形势,并提出新形势下预警信号发布工作相应的对策和措施,从而更好的做好＂气象灾害预警信号＂的发布工作,减少气象灾害所带来的损失。     

近20年我国气象灾害损失的初步分析

利用1989—2008年的全国自然灾害灾情资料,采用综合集成评价方法计算出气象灾害损失的综合指数,运用聚类分析法对近20年的气象灾害损失进行定级并分析其随时间的变化。结果显示,20年中前10年气象灾害的损失比较大,后10年损失显著减小;气象灾害导致的人口死亡数在近20年中呈明显的下降趋势;1991、1994、1996、1998年为气象灾害的重灾年。