Analysing Lava Risk for the Etnean Area: Simulation by Cellular Automata Methods

The model SCIARA, based on the Cellular Automata paradigm, is a versatile instrument whose scope is to analyse volcanic risk from lava flows.The possible fields of intervention are:[(a)] Long term forecasting of the flow direction at various eruption rates and points of emission by locating potential risk areas and permitting the creation of detailed maps of risk;[(b)] The possibility to follow the progress of an event and predict its evolution;[(c)] The verification of the possible effects of human intervention on real or simulated flows in stream deviation.A risk scenario has been developed for the Etnean territories of the towns of Nicolosi, Pedara and S. Alfio, simulating possible episodes with different vent locations along the fracture opened in the 1989 eruption and successively activated in the 1991–1993 eruption.The main characteristics of lava flows, that might be dangerous to the inhabited areas, have been analysed on the basis of the carried out Cellular Automata.     

Simulating the 1999 Capbreton canyon turbidity current with a Cellular Automata model

A numerical model has been developed for the simulation of turbidity currents driven by nonuniform, non cohesive sediment and flowing over a complex three dimensional submarine topography. The model is based on an alternative approach known as Cellular Automata paradigm. The model is validated by comparing a simulation with a reported field-scale event. The chosen case is a turbidity current which occurred in Capbreton Canyon and was initiated by a storm in December 1999. Using data from recent oceanographic cruises, the deposit of the event has been precisely described, which constrain values of model parameters. The model simulates the 1999 turbidity current over the actual canyon topography and related turbidite using three different types of particle. The model successfully simulates areas of erosion and deposition in the canyon. It predicts the vertical and longitudinal grain size evolution, and shows that the fining-up sequence can be deposited by several phases of deposition and erosion related to the current energetic variation during its evolution. This result could explain the presence of intrabed contacts or the frequent lack of facies in Bouma sequences.     

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.     

影响地震活动性因素的非均匀细胞自动机模拟研究

基于细胞自动机模型,构建了由81×81个细胞单元组成非均匀二维单断层介质样本,研究了断层结构细观非均匀性以及相关模型参数变化对模拟输出结果和强度分布特征的影响。研究结果表明：结构非均匀性是影响地震活动性的控制性参量,随着非均匀程度的增强,地震事件数量增多,震级分布变得越来越均匀,破裂演化模式由相对“脆性”向“塑性”变化;介质结构的初始条件和应力加载的随机性对地震活动演化过程基本不产生影响。此外,应力降分配系数减小使b值主体线性段向大震级延伸;随着局部摩擦损耗系数增大,模拟地震事件的数量有所增加,大震级事件数量和震级衰减增强,b值主体线性区间变窄,使断层的变形破坏方式由相对“脆性”向“塑性”变化。这些对我们理解孕震过程的复杂性是有帮助的。     

基于SD和CA的城镇土地扩展模拟模型——以江苏省南通地区为例

充分利用系统动力学模型(System Dynamics,SD)在情景模拟和宏观因素反映上的优势和元胞自动机模型(Cellular Automata,CA)在微观土地利用空间格局反映上的优势,构建一个耦合SD和CA的城镇土地扩展模拟模型,并以江苏省南通地区为例,对模型的实证应用做了进一步的验证。结果表明,这种耦合模型不仅能够对研究区域未来城镇土地扩展数量给予一个比较好的预测,而且还对其空间分布效果做了一定精度上的模拟,这使得城市规划在土地利用预测方面有一个相对科学的依据。     

基于元胞自动机民勤绿洲湖区荒漠化演化预测

民勤湖区是民勤绿洲中生态环境最为恶劣的地区,土地荒漠化问题十分突出。以民勤绿洲湖区为例,解译1992年、1998年、2002年和2006年TM卫星影像,分析其荒漠化动态变化情况,利用ArcObjects模块结合地理元胞自动机理论构造荒漠化动态模拟模型,通过对比2006年的预测数据与实际数据,对模型进行参数调整和预测检验。预测结果表明,模型预测的准确性达到90%。最后对2012年该区土地利用状况做出预测,进而对荒漠化的发展趋势进行预测分析。     

摩擦时间依从的地震活动性细胞自动机模型

设计了一个改进的单断层地震孕育过程细胞自动机（ＣＡ）模型,通过设计外界通过 施加应力与模型间进行的能量交换和模型的细胞之间存在的非线性力学作用,试图理解地震 活动特性的力学机制．与早期细胞自动机模型相比,改进了参数的取值方式,将摩擦时间依 从的理论引进模型,使该细胞自动机模型更接近实际的孕震系统．研究表明参数取值方式对 人工地震序列和各细胞破裂事件的非均匀时间特性有重要影响,较小震级和较大震级范围中 的事件分别遵从明显不同的累积频度一震级关系．