Statistical analysis of time-dependent earthquake occurrence and its impact on hazard in the low seismicity region Lower Rhine Embayment

The time-dependence of earthquake occurrence is mostly ignored in standard seismic hazard assessment even though earthquake clustering is well known. In this work, we attempt to quantify the impact of more realistic dynamics on the seismic hazard estimations. We include the time and space dependences between earthquakes into the hazard analysis via Monte Carlo simulations. Our target region is the Lower Rhine Embayment, a low seismicity area in Germany. Including aftershock sequences by using the epidemic type aftershock-sequence (ETAS) model, we find that on average the hypothesis of uncorrelated random earthquake activity underestimates the hazard by 5–10 per cent. Furthermore, we show that aftershock activity of past large earthquakes can locally increase the hazard even centuries later. We also analyse the impact of the so-called long-term behaviour, assuming a quasi-periodic occurrence of main events on a major fault in that region. We found that a significant impact on hazard is only expected for the special case of a very regular recurrence of the main shocks.     

Reliability analysis of drilled shaft behavior using finite difference method and <Emphasis Type="Italic">Monte Carlo</Emphasis> simulation

Load displacement analysis of drilled shafts can be accomplished by utilizing the “t-z” method, which models soil resistance along the length and tip of the drilled shaft as a series of springs. For non-linear soil springs, the governing differential equation that describes the soil-structure interaction may be discretized into a set of algebraic equations based upon finite difference methods. This system of algebraic equations may be solved to determine the load–displacement behavior of the drilled shaft when subjected to compression or pullout. By combining the finite difference method with Monte Carlo simulation techniques, a probabilistic load–displacement analysis can be conducted. The probabilistic analysis is advantageous compared to standard factor of safety design because uncertainties with the shaft–soil interface and tip properties can be independently quantified. This paper presents a reliability analysis of drilled shaft behavior by combining the finite difference technique for analyzing non-linear load–displacement behavior with Monte Carlo simulation method. As a result we develop probabilistic relationships for drilled shaft design for both total stress (undrained) and effective stress (drained) parameters. The results are presented in the form of factor of safety or resistance factors suitable for serviceability design of drilled shafts.     

Time independent seismic hazard analysis in Alborz and surrounding area

The Bayesian probability estimation seems to have efficiencies that make it suitable for calculating different parameters of seismicity. Generally this method is able to combine prior information on seismicity while at the same time including statistical uncertainty associated with the estimation of the parameters used to quantify seismicity, in addition to the probabilistic uncertainties associated with the inherent randomness of earthquake occurrence. In this article a time-independent Bayesian approach, which yields the probability that a certain cut-off magnitude will be exceeded at certain time intervals is examined for the region of Alborz, Iran, in order to consider the following consequences for the city of Tehran. This area is located within the Alpine-Himalayan active mountain belt. Many active faults affect the Alborz, most of which are parallel to the range and accommodate the present day oblique convergence across it. Tehran, the capital of Iran, with millions of inhabitants is located near the foothills of the southern Central Alborz. This region has been affected several times by historical and recent earthquakes that confirm the importance of seismic hazard assessment through it. As the first step in this study an updated earthquake catalog is compiled for the Alborz. Then, by assuming a Poisson distribution for the number of earthquakes which occur at a certain time interval, the probabilistic earthquake occurrence is computed by the Bayesian approach. The highest probabilities are found for zone AA and the lowest probabilities for zones KD and CA, meanwhile the overall probability is high.     

Simultaneous identification of a single pollution point-source location and contamination time under known flow field conditions

A theoretical framework is presented that allows direct identification of a single point-source pollution location and time in heterogeneous multidimensional systems under known flow field conditions. Based on the concept of the transfer function theory, it is shown that an observed pollution plume contains all the necessary information to predict the concentration at the unknown pollution source when a reversed flow field transport simulation is performed. This target concentration C₀ is obtained from a quadratic integral of the observed pollution plume itself. Backwards simulation of the pollution plume leads to shrinkage of the C₀-contour due to dispersion. When the C₀-contour reduces to a singular point, i.e. becomes a concentration maximum, the position of the pollution source is identified and the backward simulation time indicates the time elapsed since the contaminant release. The theoretical basis of the method is first developed for the ideal case that the pollution plume is entirely known and is illustrated using a synthetic heterogeneous 2D example where all the hydro-dispersive parameters are known. The same example is then used to illustrate the procedure for a more realistic case, i.e. where only few observation points exist.     

Stochastic modelling of soil moisture dynamics in a grassland of Qilian Mountain at point scale

Stochastic modeling of soil moisture dynamics is crucial to the quantitative understanding of plant responses to water stresses,hydrological control of nutrient cycling processes,water competition among plants,and some other ecological dynamics,and thus has become a hotspot in ecohydrology at present.In this paper,we based on the continuously monitored data of soil moisture during 2002―2005 and daily precipitation date of 1992―2006,and tried to make a probabilistic analysis of soil moisture dynamics at point scale in a grassland of Qilian Mountain by integrating the stochastic model improved by Laio and the Monte Carlo method.The results show that the inter-annual variations for the soil moisture patterns at different depths are very significant,and that the coefficient of variance(CV) of surface soil moisture(20 cm) is almost continually kept at about 0.23 whether in the rich or poor rainy years.Interestingly,it has been found that the maximal CV of soil moisture has not always appeared at the surface layer.Comparison of the analytically derived soil moisture probability density function(PDF) with the statistical distribution of the observed soil moisture data suggests that the stochastic model can reasonably describe and predict the soil moisture dynamics of the grassland in Qilian Mountain at point scale.By extracting the statistical information of the historical precipitation data in 1994―2006,and inputting them into the stochastic model,we analytically derived the long-term soil moisture PDF without considering the inter-annual climate fluctuations,and then numerically derived the one when considering the inter-annual fluctuation effects in combination with a Monte-Carlo procedure.It was found that,though the peak position of the probability density distribution significantly moved towards drought when considering the disturbance forces,and its width was narrowed,accordingly its peak value was increased,no significant bimodality was observed in the soil moisture dynamics under the given intensity of random fluctuation disturbance.     

A derived probability distribution approach to stormwater quality modeling

The closed-form analytical stormwater quality models are developed for simulating urban catchment pollutant buildup and washoff processes. By integrating the rainfall–runoff transformation with pollutant buildup and washoff functions, stormwater quality measures, such as the cumulative distribution functions (CDFs) of pollutant loads, the expected value of pollutant event mean concentrations (EMCs) and the average annual pollutant load can be derived. This paper presents methodologies and major procedures for the development of urban stormwater quality models based on derived probability distribution theory. In order to investigate the spatial variation in model parameters and its impact on stormwater pollutant buildup and washoff processes as well as pollutant loads to receiving waters, an extended form of the original rainfall–runoff transformation which is based on lumped runoff coefficient approach is proposed to differentiate runoff generation mechanisms between the impervious and pervious areas of the catchment. In addition, as a contrast to the aggregated pollutant buildup models formulated with a single lumped buildup parameter, the disaggregated form of the pollutant buildup model is proposed by introducing a number of physically-based parameters associated with pollutant buildup and washoff processes into the pollutant load models. The results from the case study indicate that analytical urban stormwater management model are capable of providing results in good agreement with the field measurements, and can be employed as alternatives to continuous simulation models in the evaluation of long-term stormwater quality measures.     

岩体质量分级的风险分析方法

提出了基于RMR岩体质量分级系统的岩体质量研究风险分析方法。该方法分析步骤如下 :(1)通过岩芯样品的现场观测和实验室试验获得分类所需的变量 ;(2 )统计分析拟合得出各变量的分布函数及参数 ;(3)运用Monte Carlo模拟方法获得 2万个RMR值 ,并将结果绘成岩体质量描述图 ;(4)利用以上结果作出岩体质量风险分析评价。该方法用于润扬长江公路大桥岩体质量评价研究获得良好效果     

景像匹配仿真的一种新方法

分析了影响景像相关匹配精度的各种误差因素，并给出它们的误差仿真模型，该模型可以适应飞行姿态、飞行器特性，天候等条件变化时的匹配概率估计，并可以与图像特征参数分析方法相结合。实验验证了该模型的有效性，且可以快速地给出影像图的适配性估计图，用于飞行器的航迹规划。     

测震学多项指标综合预测概率分析

通过对测震学各单项指标的预测效能调研，为进一步提取前兆信息，选择了7项测震学指标：频次、地震蠕变、6值、缺震、η值、GL值和调制比，进行综合概率分析。7项指标对关注地区的全时空扫描并考虑了空间单元异常与中强震地点对应的模糊关系，得到指标在各空间单元异常后发生中强震的条件概率。根据历史上每个单项指标的预报效能求计算综合概率时的指标权重，按贝叶斯定律得到相应不同指标在不同时间窗和不同空间单元时中强震发生的加权综合概率。计算结果（1970年以来）表明，对华北地区和川滇地区这一综合概率方法预测效能的R值评估超过0.5。     

三峡工程建成后枯水期运行的气候风险研究

通过蒙特卡罗试验, 探讨了三峡工程建成后枯水期运行风险的评估方法。以GCM模拟试验结果为未来气候情景, 随机模拟了三峡地区在该气候情景下枯水期月降水量分布; 建立了三峡地区月径流-降水模型和三峡水库调度模型; 初步分析了长江三峡工程建成后在当前气候背景和可能未来气候情景下的运行风险。结果表明, 三峡水库的运行对气候变化反应敏感, 春季和冬季的发电风险有明显改变。