通过Napa地震探析美国的地震应急

结合美国北加州纳帕(Napa)地震,系统地介绍了美国政府机关和科研机构的地震应急工作的完整流程:从地震仪接收到地震产生的P波开始,地震预警系统发出警报,到震后美国地质调查局(USGS)在线烈度调查系统(DYFI)采集民众地震烈度报告,再到地震快速评估系统(PAGER)快速估算地震伤亡和经济损失情况,发布警报级别,最后进行实时余震发震概率预测。积极利用民众力量、信息共享以及自动计算是美国地震应急工作流程的突出特点。     

Evaluation of earthquake signal characteristics for early warning

This paper evaluates different characteristics for earthquake early warning.The scaling relationships between magnitude,epicenter distance and calculated parameters are derived from earthquake event data from USGS.The standard STA/LTA method is modified by adding two new parameters to eliminate the effects of the spike-type noise and small pulsetype noise ahead of the onset of the P-wave.After the detection of the P-wave,the algorithm extracts 12 kinds of parameters from the first 3 seconds of the P-wave.Then stepwise regression analysis of these parameters is performed to estimate the epicentral distance and magnitude.Six different parameters are selected to estimate the epicentral distance,and the median error for all 419 estimates is 16.5 km.Four parameters are optimally combined to estimate the magnitude,and the mean error for all events is 0.0 magnitude units,with a standard deviation of 0.5.Finally,based on the estimation results,additional work is proposed to improve the accuracy of the results.     

一种实时场地校正方法及其在地震预警中的应用

地震预警系统对地震数据处理的实时性要求极高。其系统数据来源除布设在基岩的测震台站外,还有大量非基岩场地的强震动台站和地震烈度仪台站,其场地影响不容忽视。为了考虑震级估算和地震动场预测中的场地影响,需实时对各种场地条件下的地震波形进行校正。目前处理一般使用某个标量来表征场地放大效应。本文采用一种实时的场地校正方法,首先计算目标场地与参考场地的谱比,然后通过最小二乘法、双线性变换将谱比转化为因果递归的无限冲激响应(IIR)时域滤波器,之后可以应用该滤波器进行实时场地校正。该方法考虑了场地放大系数的频率依赖性,相比于标量校正提高了准确度。应用我国四川和日本部分强震动台站记录,验证并讨论了这种实时场地校正方法在地震预警中的应用效果。     

One-station estimates of seismic moments from the mantle magnitudeM m: The case of the regional field (1.5°≤Δ≤15°)

We extend to the regional field of distances the procedure of one-station estimation of seismic moments using the mantle magnitudeM _m, as introduced earlier in the case of teleseismic events. A theoretical analysis of the validity of the asymptotic expansion of normal modes in terms of surface waves, which was used in the development ofM _m, upholds the validity of the algorithm for distances as short as 1.5°. This is confirmed by the analysis of a dataset of 149 GEOSCOPE records obtained at distances ranging from 1.5 to 15°, from earthquakes with moments between 10²⁴ and 2.5×10²⁷ dyn-cm. The performance ofM _m as measured in terms of average residual with respect to published values ofM ₀, and standard deviation of the residuals, is not degraded in this distance range, with respect to the teleseismic case. This indicates that the mantle magnitudeM _mcan be reliably used at regional distances, notably for tsunami warning applications.     

16选X地震报警器

地震报警是缩短地震速报时间的关键,本文介绍了适合遥测地震台网使用的１６选Ｘ地震报警器的工作原理和使用方法,并提出了电原理图,便于仿制,或根据需要作相应改变,以满足不同场合的要求。     

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.     

基于码率控制的DMB预警信息预处理系统

为解决预警信息音频广播的单一性,通过对数字多媒体广播(DMB)的标准研究,设计了基于码率控制的DMB预警信息预处理系统.该系统采用MPEG-4 HE AAC和H.264/AVC编码算法对预警音视频信息分别进行信源编码,实现将编码后信息合成为TS码流;采用RS和卷积交织的信道编码方法实现TS码流的纠错控制,提高传输可靠性.针对传输码率不稳定、音视频传输容量和速率不匹配的技术难点,提出基于码率控制的音视频匹配控制传输方法,通过空包插入法实现对编码输出数据码率的智能控制,达到音视频预警信息的稳定实时输出.该预处理系统目前已通过验证,可显著提高预警信息传输的可靠性、稳定性和实时性.     

利用2014年云南地震验证与研究四川地震预警快速震级估算模型

地震预警系统是防震减灾中最为行之有效的方法之一,其中对地震震级的估算是非常重要且困难的。目前,比较成熟的地震震级估计方法包括：基于最大卓越周期（τ_p^max）、特征周期（τ_c）和最大位移幅值（P_d）方法。利用2014年云南地3次大地震主震及余震P波初期部分的信息,验证与研究了四川地区地震预警快速震级估算模型在云南地区的适用性,结果表明3种参数模型均能在短时间内有效地进行震级估算。对于本研究数据库而言,P_d-4 s时窗模型最优,3个参数模型求得的估计震级在大震下均没有出现明显的震级饱和现象。但由于目前难以在短时窗下得到准确的震源/中距,因此推荐在云南地区地震预警系统中使用τ_p^max和τ_c模型来估计震级。     

Literature analysis of Dendrolimus disasters based on remote sensing monitoring

Due to global climate change, Dendrolimus pests and diseases seriously threaten the protection of forestry plants and the safety of crops all over the world. This paper aims to discuss the research results and frontier progress of Dendrolimus disasters based on remote sensing monitoring, trying to find the occurrence characteristics of pests. In this paper, bibliometric methods and CiteSpace knowledge graphs were used to analyze the publication trend, highly cited documents, key research institu...     

地震预警现地PGV连续预测的最小二乘支持向量机模型

为提升现地仪器地震烈度预测的准确性与连续性,研究面向地震预警的PGV连续预测模型.以中国仪器地震烈度标准的计算参数：0.1~10 Hz带通滤波三分向矢量合成速度峰值PGV为预测目标,利用日本K-net与KiK-net台网P波触发后1~10 s强震数据,基于人工智能中的机器学习方法-最小二乘支持向量机,选取7种特征参数作为输入构建最小二乘支持向量机PGV预测模型LSSVM-PGV.结果表明,本文建立的LSSVM-PGV模型在训练数据集与测试数据集上的预测误差标准差变化趋于一致,具备泛化性能;P波触发后3 s预测PGV与实测PGV即可整体符合1：1关系,随着时间窗的增长,PGV预测的误差标准差显著减小、并在P波触发后6 s趋向收敛,具备准确连续预测能力;对比同为P波触发后3 s的常用Pd-PGV模型,LSSVM-PGV模型的PGV预测误差标准差明显减小,"小值高估"与"大值低估"现象明显改善,预测准确性得到提升.熊本地震序列的震例分析表明,对于6.5级以下地震,LSSVM-PGV模型最多在P波触发后3 s即可预测出与实测PGV整体符合1：1关系的PGV;对于7.3级主震,由于其破裂过程的复杂性,P波触发后3 s的预测结果出现一定程度的低估,但随着时间窗增长至6 s时,预测PGV与实测PGV符合1：1关系、并直到10 s整体趋势保持一致.本文构建的LSSVM-PGV模型可用于现地地震预警仪器地震烈度的预测.