Short Term and Short Range Seismicity Patterns in Different Seismic Areas of the World

The aim of this work is to quantitatively set up a simple hypothesis for occurrence of earthquakes conditioned by prior events, on the basis of a previously existing model and the use of recent instrumental observations. A simple procedure is presented in order to determine the conditional probability of pairs of events (foreshock-mainshock, mainshock-aftershock) with short time and space separation. The first event of a pair should not be an aftershock, i.e., it must not be related to a stronger previous event. The Italian earthquake catalog of the Istituto Nazionale di Geofisica (ING) (1975–1995, M 3.4), the earthquake catalog of the Japan Meteorological Agency (JMA) (1983–1994, M 3.0) and that of the National Observatory of Athens (NOA) (1982–1994, M 3.8) were analyzed. The number of observed pairs depends on several parameters: the size of the space-time quiescence volume defining nonaftershocks, the inter event time, the minimum magnitude of the two events, and the spatial dimension of the alarm volume after the first event. The Akaike information criterion has been adopted to assess the optimum set of space-time parameters used in the definition of the pairs, assuming that the occurrence rate of subsequent events may be modeled by two Poisson processes with different rates: the higher rate refers to the space-time volume defined by the alarms and the lower one simulates earthquakes that occur in the nonalarm space-time volume. On the basis of the tests carried out on the seismic catalog of Italy, the occurrence rate of M 3.8 earthquakes followed by a M 3.8 mainshock within 10 km and 10 days (validity) is 0.459. We have observed, for all three catalogs, that the occurrence rate density for the second event of a couple (mainshock or aftershock) of magnitude M₂ subsequent to a nonaftershock of magnitude M₁ in the time range T can be modeled by the following relationship: (T, M₂) = 10^{a + b(M1 - M2)} with b varying from 0.74 (Japan) to 1.09 (Greece). The decrease of the occurrence rate in time for a mainshock after a foreshock or for large aftershocks after a mainshock, for all three databases, obeys the Omori's law with p changing from 0.94 (Italy) to 2.0 (Greece).     

利用标准时频变换方法在强噪声环境下无偏拾取地震P波、S波到时

地震P波、S波到时是精确分析地震水平位置、深度与速度结构等的重要参数,如何准确拾取P波和S波到时是地震学的一项重要的基础工作.大数据量与强噪声环境给地震到时的自动拾取带来了很大挑战.在频率域中可将信号与噪声分离,但会造成震相的偏移.针对上述问题,本文在STA/LTA、AIC方法的基础上,引入了标准时频变换（Normal Time-Frequency Transform,NTFT）,结合信号时间域与频率域特征,提出了基于NTFT的STA/LTA方法,以及基于NTFT的AIC方法来拾取P波和S波的到时.基于NTFT的STA/LTA方法通过构建即时频率约束的特征函数,以增强地震信号振幅响应的变化特征.基于NTFT的AIC方法则根据NTFT的变换系数定位即时频率-时间基准点,通过滑动窗口直接对标准时频谱进行AIC处理拾取最佳到时.本文采用了不同强度噪声的60组合成数据和105组实测地震数据对方法的可靠性进行检验.以人工拾取到时为参考,实测数据中NTFT-STA/LTA方法拾取P波、S波到时的均方根误差分别为0.36 s和0.56 s;NTFT-AIC方法拾取P波、S波到时的均方根误差分别为0.25 s和0.35 s.相比于STA/LTA、AIC方法,NTFT改进后的方法提高了P波和S波到时的拾取准确率,为强噪声环境下的地震波形到时拾取提供了新思路.

     

气候变化对北方农牧交错带界线变迁影响的定量探测方法研究

气候对北方农牧交错带界线变迁的定量影响是目前生态脆弱敏感区对气候变化响应领域的研究热点问题。前人已在气候变化对农牧交错带界线的定性影响方面有较为深刻的认识,但仍缺乏在时间和空间上对气候贡献率进行有针对性的定量辨识。本文利用1970年以来长时间序列的国家气象站点数据和土地利用遥感解译数据,分别提取了基于气候要素和土地利用的20世纪70年代、80年代、90年代和21世纪前10年4个时期的北方农牧交错带界线,通过垂直和水平方向变动探测方法（FishNet）和界线变迁方向变动探测方法（DSAS）对气候界线与土地利用界线的时空变化进行探测,定量分析了不同时期气候对农牧交错带界线变迁影响的贡献率。结果表明,气候与土地利用界线空间分布格局及气候贡献率在不同时期、不同区域差异较大,在西北地区变幅最小,东北地区变幅最大。在大兴安岭东南缘农田控制水源涵养生态功能区西北段以及内蒙古高原东南缘农、林、牧业生态—生产功能区西北段,气候与土地利用界线空间耦合关系最为密切,在该地区基于FishNet方法下水平方向上气候贡献率达10.7%~44.4%,垂直方向上达4.7%~55.9%;基于DSAS方法下气候贡献率为1.1%~16.8%。两种方法探测结果大部分趋于一致,但DSAS方法精度高,适用于小范围精确探测;FishNet方法更简单,适用于精度要求不高、快速直观的统计分析。本研究可为北方农牧交错带内农牧业生产适应气候变化、合理开发土地生产潜力、保护农牧交错带区内生态环境提供科学依据和指导。     

Improving rainfall–runoff modelling through the control of uncertainties under increasing climate variability in the Ouémé River basin (Benin,West Africa)

ABSTRACT

The objective of this paper is to understand how the natural dynamics of a time-varying catchment, i.e. the rainfall pattern, transforms the random component of rainfall and how this transformation influences the river discharge. To this end, this paper develops a rainfall–runoff modelling approach that aims to capture the multiple sources and types of uncertainty in a single framework. The main assumption is that hydrological systems are nonlinear dynamical systems which can be described by stochastic differential equations (SDE). The dynamics of the system is based on the least action principle (LAP) as derived from Noether’s theorem. The inflow process is considered as a sum of deterministic and random components. Using data from the Ouémé River basin (Benin, West Africa), the basic properties for the random component are considered and the triple relationship between the structure of the inflowing rainfall, the corresponding SDE that describes the river basin and the associated Fokker-Planck equations (FPE) is analysed.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR D. Gerten     

用于地震预警的P波震相到时自动拾取

P波震相的自动拾取可用于地震预警中地震事件判别和地震定位,是实现基于地震台网地震预警的首要条件.针对地震预警中P波震相拾取的特点,本文发展了一套基于长短时平均(STA/LTA)和池赤准则(AIC)算法的多步骤P波自动拾取技术,应用Delaunay三角剖分提出了一种非几何相关的干扰信号剔除方法,并应用福建省数字地震台网记录对方法进行了验证,目前方法已经用到了福建省地震预警试验系统中.     

补偿海空重力测量动态效应剩余影响的通用模型

针对目前作业过程中普遍存在的测量动态环境效应剩余影响问题,在深入分析海空重力测量误差源形成机理及其变化特性基础上,提出了一种适用于补偿各类海空重力仪动态效应剩余影响的通用模型;研究探讨了通用模型形式优选和模型参数估计问题,将基于信息论的Akaike信息量准则引入通用模型表达式的优选过程,提出应用互相关分析方法对模型参数进行估计,在双重约束下构建了补偿动态效应剩余影响的优化模型。使用典型动态环境下的海面重力观测数据对该方法的有效性进行了验证,结果显示,海洋重力测量成果内符合精度从原先的±9.35×10^-5 m/s²大幅提升到±1.01×10^-5 m/s²,充分体现了本文方法和模型对消除高动态测量环境效应影响的优良特性。     

顾及次优噪声模型的GNSS坐标时间序列噪声模型选择

在全球导航卫星系统（Global Navigation Satellite System,GNSS）坐标时间序列噪声建模领域,选择合适的噪声模型对GNSS坐标时间序列的速度信号提取具有重要价值.长期以来,研究者专注于建立最优噪声模型来描述GNSS坐标时间序列中的噪声成分,却往往直接忽略与最优噪声模型性能接近的次优噪声模型.本文选用8种常见的噪声模型,使用极大似然估计法（Maximum Likelihood Estimate,MLE）估计模型参数,以赤池信息量准则（Akaike information criterion,AIC）作为评价准则来选取噪声模型.实验数据采用中国区域12个国际GNSS服务（International GNSS Service,IGS）基准站36个坐标分量及全球范围内50个IGS基准站150个坐标分量的坐标时间序列.结果表明,超过半数的测站坐标分量上存在与最优噪声模型性能接近的次优噪声模型.在此基础上中国区域的IGS站,在东方向有14%的次优噪声模型拥有比最优噪声模型数值更大的速度不确定度,在北方向和垂直方向,这一值分别为33%和63%.而对于全球范围的IGS站,这一值分别为31%、39%和48%.因此在GNSS坐标时间序列噪声模型选择过程中,充分考虑与最优噪声模型性能接近的次优噪声模型有助于获得到更保守的估计结果.

     

强噪声环境下基于信噪比的地震P波到时自动提取方法

大数据量、强噪声环境给地震P波到时的自动提取带来很大挑战.针对此问题,本文通过构建特殊的特征函数,建立SNR与STA/LTA的内在联系,提出两种基于SNR的地震P波到时自动提取方法,即基于SNR的STA/LTA方法与基于SNR的综合方法.这两种方法分别是运用SNR概念对传统STA/LTA方法和STA/LTA与AIC综合方法的改进.仿真分析结果表明：对于弱噪声环境（10 dB）和一般噪声环境（6 dB）,本文方法较传统STA/LTA方法对地震P波到时提取的准确度更高;而对于强噪声环境（3 dB）,本文方法仍能准确提取地震P波到时,而传统STA/LTA方法则出现了较大的误判率（10%）与漏判率（65%）.本文方法为STA/LTA赋予了明确的物理意义,使其阈值的选取建立在严密的数学推导之上.另外,本文方法在进行地震P波到时自动提取的同时,兼具数据预处理功能,无需额外的基线校正或高通滤波,因而具有较好的实时性.

     

基于AIC准则的RBF神经网络在GPS高程拟合中的应用

本文采用AIC准则优化RBF神经网络参数的方法进行GPS高程拟合,在建立网络模型过程中,对不同的聚类半径由最近邻聚类法求出不同类别的聚类数目及相应的聚类中心和初始扩展常数,通过对不同类别分别进行调整扩展常数的网络训练,求出其最小AIC值,再根据AIC准则确定结构最优的RBF网络模型。实验结果表明:这种方法为确定最优RBF网络模型的隐节点数目及相应参数提供了途径;拟合精度较高,在较平坦测区可以替代三等水准测量。     

Model averaging versus model selection: estimating design floods with uncertain river flow data

ABSTRACT

This study compares model averaging and model selection methods to estimate design floods, while accounting for the observation error that is typically associated with annual maximum flow data. Model selection refers to methods where a single distribution function is chosen based on prior knowledge or by means of selection criteria. Model averaging refers to methods where the results of multiple distribution functions are combined. Numerical experiments were carried out by generating synthetic data using the Wakeby distribution function as the parent distribution. For this study, comparisons were made in terms of relative error and root mean square error (RMSE) referring to the 1-in-100 year flood. The experiments show that model averaging and model selection methods lead to similar results, especially when short samples are drawn from a highly asymmetric parent. Also, taking an arithmetic average of all design flood estimates gives estimated variances similar to those obtained with more complex weighted model averaging.