A way to synchronize models with seismic faults for earthquake forecasting: Insights from a simple stochastic model

Numerical models are starting to be used for determining the future behaviour of seismic faults and fault networks. Their final goal would be to forecast future large earthquakes. In order to use them for this task, it is necessary to synchronize each model with the current status of the actual fault or fault network it simulates (just as, for example, meteorologists synchronize their models with the atmosphere by incorporating current atmospheric data in them). However, lithospheric dynamics is largely unobservable: important parameters cannot (or can rarely) be measured in Nature. Earthquakes, though, provide indirect but measurable clues of the stress and strain status in the lithosphere, which should be helpful for the synchronization of the models.The rupture area is one of the measurable parameters of earthquakes. Here we explore how it can be used to at least synchronize fault models between themselves and forecast synthetic earthquakes. Our purpose here is to forecast synthetic earthquakes in a simple but stochastic (random) fault model. By imposing the rupture area of the synthetic earthquakes of this model on other models, the latter become partially synchronized with the first one. We use these partially synchronized models to successfully forecast most of the largest earthquakes generated by the first model. This forecasting strategy outperforms others that only take into account the earthquake series. Our results suggest that probably a good way to synchronize more detailed models with real faults is to force them to reproduce the sequence of previous earthquake ruptures on the faults. This hypothesis could be tested in the future with more detailed models and actual seismic data.     

Towards Formulation of a Space-borne System for Early Warning of Floods: Can Cost-Effectiveness Outweigh Prediction Uncertainty?

The three most important components necessary for functioning of an operational flood warning system are: (1) a rainfall measuring system; (2) a soil moisture updating system; and, (3) a surface discharge measuring system. Although surface based networks for these systems can be largely inadequate in many parts of the world, this inadequacy particularly affects the tropics, which are most vulnerable to flooding hazards. Furthermore, the tropical regions comprise developing countries lacking the financial resources for such surface-based monitoring. The heritage of research conducted on evaluating the potential for measuring discharge from space has now morphed into an agenda for a mission dedicated to space-based surface discharge measurements. This mission juxtaposed with two other upcoming space-based missions: (1) for rainfall measurement (Global Precipitation Measurement, GPM), and (2) soil moisture measurement (Hydrosphere State, HYDROS), bears promise for designing a fully space-borne system for early warning of floods. Such a system, if operational, stands to offer tremendous socio-economic benefit to many flood-prone developing nations of the tropical world. However, there are two competing aspects that need careful assessment to justify the viability of such a system: (1) cost-effectiveness due to surface data scarcity; and (2) flood prediction uncertainty due to uncertainty in the remote sensing measurements. This paper presents the flood hazard mitigation opportunities offered by the assimilation of the three proposed space missions within the context of these two competing aspects. The discussion is cast from the perspective of current understanding of the prediction uncertainties associated with space-based flood prediction. A conceptual framework for a fully space-borne system for early-warning of floods is proposed. The need for retrospective validation of such a system on historical data comprising floods and its associated socio-economic impact is stressed. This proposal for a fully space-borne system, if pursued through wide interdisciplinary effort as recommended herein, promises to enhance the utility of the three space missions more than what their individual agenda can be expected to offer.     

基于模糊综合评判的动态路径行程时间预测模型

针对城市交通路网的复杂性和不确定性,提出一种基于模糊综合评判的动态行程时间预测模型,将总行程时间分为行驶时间和交通延误时间两部分,分别介绍这两部分时间的预测模型,并利用该模型对一组模拟道路信息和路况信息进行实际预测,对预测结果进行比较和分析。研究表明该模型算法简捷实用,预测结果精度较高。     

Verification of the motion fields over Southeast Asia by the Florida State University (FSU) superensemble forecast

The Florida State University (FSU) multimodel superensemble forecast is evaluated against several other operational weather models for the Southeast Asia region. The superensemble technique has demonstrated its exceptional skills in forecasting precipitation, motion and mass fields compared to either individual global operational or ensemble mean forecasts. The motion field investigation for the season of 2001 reveals that the superensemble forecasts are closer to the observed data compared to the other global member operational models through its low systematic errors at the 850 hPa level. The FSU multimodel superensemble forecasts exhibit the lowest root mean square errors (RSMEs), the highest correlation against the best observed data and the lowest systematic errors compared to the other operational model members. These forecasts have the potential to provide better daily weather predictions over the Southeast Asia region, particularly during the early northeast monsoon that often causes heavy rainfall in the equatorial part of the Southeast Asia region.     

Fission track evidence for the Mesozoic Cenozoic tectonic uplift of Mt. Bogda, Xinjiang, Northwest China

1 IntroductionThe Mesozoic-Cenozoic tectonic evolution and ki-netics mechanism of the intracontinental orogen are thekey subjects of continental dynamics (Ma Zongjin andGao Xianglin, 2004) and the key to understanding theregional geological tectonics (Qia…     

基于预测的边缘检测方法

提出了一种基于预测的、有一定自适应性的边缘检测方法。介绍了其原理和算法实现过程。通过计算两个相邻像素的灰度值的均值、均方差和梯度来预测下一个像素的灰度值，比较预测值和真实值来判断下一个像素是否是边界点。通过与现有同类算法的比较，证明了该算法的优越性。     

地震属性分析中水平切片的应用

利用地震数据体中含有的丰富地质信息,可以有效地进行储层预测。层拉平水平切片地层学解释方法是先将地震剖面目的层段做层拉平处理,然后对切片顺地层层面追踪,勾绘出各种地层现象,并以地层学的观点加以解释。该方法在吉林探区扶新南部地区的应用中,对于识别河道的展布趋势取得了较好的效果,而且发现了多期叠置的扇型沉积体。另外,还可指导反演数据体的解释,做到对岩性体从定性到定量的描述。     

一种基于核学习的储集层渗透率预测新方法

基于核学习的支持向量机,是一种采用结构风险最小化原则代替传统经验风险最小化原则的新型统计学习方法,具有完备的理论基础。这里提出了核学习技术在储集层非均质特性描述中渗透率参数预测的新用途。在复杂地层中,基于支持向量机的智能和自适应模式识别能力而建立了常规测井多参数信息输入的渗透率预测模型,然后对实际油田储集层渗透率进行了预测。与常规线性回归模型预测结果相对比,所提出的方法更易于使用,很少受不确定因素的影响,并具有较强的信息整合能力以及更高的预测准确性和可信度。     

现阶段地表油气化探技术难题与发展对策

虽然地表油气化探方法技术已取得显著的应用效果, 但是由于成功率计算标准不同及方法技术本身的缺陷, 导致人们对方法的认同度较低。当前, 地表油气化探技术的发展, 一方面要以可靠的实验依据、严谨的数理推导及理论模型应对来自方法技术本身的挑战, 另一方面也要利用其快速、廉价和直接的优势, 加强与地质、遥感、非震物探等方法综合应用。     

低频泥石流特征及防治 --以四川汶川县茶园沟为例

低频泥石流指30a以上发生1次的泥石流。尽管发生频率很低，但由于自身的特征及人们认识上的原因，其造l戒的人员伤亡和财产损失却居各类泥石流之首。对低频泥石流的研究在预防和减轻泥石流灾害方面有着重要意义。文章以2003年8月9日发生在四川汶川县茶园沟的泥石流为蒯，采用形态调查法和称重法等方法确定了流量、流速及重度。分析了其物质来源及形成的自然和人为原因，探讨了低频泥石流的特征。针对低频泥石流的低频性、破坏性和隐蔽性特点，同时考虑到低频泥石流沟的防治受保护对象的重要程度及资金投入等因素的限制，提出了进行泥石流危险性分区、搞好小流域水土深持、普及泥石流防灾减灾知识及加强监测和预警预报等措施，这对减轻低频泥石流区的灾害有一定的借鉴意义。