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1.
The classical extreme value theory based on generalized extreme value (GEV) distribution and generalized Pareto distribution (GPD) is applied to the wave height estimate based on wave hindcast data covering a period of 31?years for a location in the eastern Arabian Sea. Practical concern such as the threshold selection and model validation is discussed. Estimates of wave height having different return periods are compared with estimates obtained from different distributions. On comparing the distributions fitted to the GEV with annual maximum approach and GPD with peaks over threshold approach have indicated that both GEV and GPD models gave similar or comparable wave height for the study area since there is no multiple storm event in a year. Influence of seasonality on wave height having different return period is also studied. 相似文献
2.
Conditional Simulation of Random Fields with Bivariate Gamma Isofactorial Distributions 总被引：5，自引：0，他引：5
Xavier Emery 《Mathematical Geology》2005,37(4):419-445
This work focuses on a random function model with gamma marginal and bivariate isofactorial distributions, which has been applied in mining geostatistics for estimating recoverable reserves by disjunctive kriging. The objective is to widen its use to conditional simulation and further its application to the modeling of continuous attributes in geosciences. First, the main properties of the bivariate gamma isofactorial distributions are analyzed, with emphasis in the destructuring of the extreme values, the presence of a proportional effect (higher variability in high-valued areas), and the asymmetry in the spatial correlation of the indicator variables with respect to the median threshold. Then, we provide examples of stationary random functions with such bivariate distributions, for which the shape parameter of the marginal distribution is half an integer. These are defined as the sum of squared independent Gaussian random fields. An iterative algorithm based on the Gibbs sampler is proposed to perform the simulation conditional to a set of existing data. Such ‘multivariate chi-square’ model generalizes the well-known multigaussian model and is more flexible, since it allows defining a shape parameter which controls the asymmetry of the marginal and bivariate distributions. 相似文献
3.
Analysis of random anisotropic damage mechanics problems of rock mass 总被引：10，自引：0，他引：10
Summary A probabilistic analysis method of random anisotropic damage mechanics problems is proposed in parts I and II. In part I, based on the measured characteristics of random crack distribution on the surface of a rock specimen, a probabilistic distribution law of damage variables for rock mass is presented as a Beta distribution by using the Monte-Carlo statistical simulation method. In part II, statistical estimation of a damage state and properties of random damaged rock mass are evaluated by Rosenblueth's point estimate method. Combining with the F. E. method, rock mechanics problem for random damaged state have been analyzed. 相似文献
4.
利用西藏珠穆朗玛峰地区5个气象站点1971-2012年逐日降水量资料,采用滑动平均、线性回归、Mann-Kendall非参数检验和Morlet小波分析等方法,分析了珠穆朗玛峰地区极端降水事件的时空变化特征. 结果表明：1971-2012年42 a来,珠穆朗玛峰地区大部分极端降水指数呈现出自东向西逐渐增大的空间分布格局, 连续干旱日数、连续湿日和降水强度表现为增加趋势,其他极端降水指数趋于减少. 其中,强降水量、极强降水量和年降水总量减幅较大,分别为-5.74 mm·（10a）-1、-1.20 mm·（10a）-1和-5.32 mm·（10a）-1,在喜马拉雅山南坡的聂拉木站表现的最为明显. 大部分极端降水指数在21世纪最初的10 a减幅最大,在30 a际尺度上也表现为减少趋势. 除连续干旱日数外,极端降水与年降水总量关系密切. 各项极端降水指数都存在3～4 a显著周期,也存在10 a、12 a和15 a的周期. 在时间转折上,各项极端降水指数均未发生气候突变. 相似文献
5.
针对确定性模型难以描述含水层非均质空间分布的问题,提出基于随机理论的地下水环境风险评价方法。以矩形场地地下水污染风险评价为例,采用蒙特卡罗法生成大量渗透系数随机场,模拟含水层参数各种可能的非均质空间分布,在此基础上建立场地地下水流模型与溶质运移模型,分别计算污染物在地下水中的迁移转化情况。统计大量随机模拟中污染事故发生的频率,当模拟次数足够多时,污染频率收敛于污染概率,污染风险即通过污染概率体现出来。该方法将模型参数设为满足一定分布特征的随机变量,避免了确定性方法得出的武断的评价结果,可为工厂的选址、水源地的选址等工作提供科学指导。 相似文献
6.
Occurrence of dry and wet days in the Brahmaputra Valley has been studied using a first-order Markov Chain model. The model is fitted to the daily rainfall series recorded at ten stations widely distributed in the valley. The adequacy of the model is tested and found suitable. At all the stations, dry and wet spells having different durations follow geometric distribution. For pre-monsoon and monsoon seasons, the expected dry and wet days, the expected length of a weather cycle and the return period of dry spells having different, durations are calculated, and the results for different stations are compared. 相似文献
7.
Foundation settlement statistics via finite element analysis 总被引：5，自引：0，他引：5
The dispersion observed in soil data comes both from the spatial variability which greatly influences the behavior of large structures and from errors in testing. Thus, the geotechnical engineering deals with uncertainties for which deterministic approaches are not suitable. The resort to probabilistic techniques, enables modeling uncertainties by analyzing their dispersion effect on the global behavior of the structure. The scope of this paper is analyzing settlement and differential settlement variability of a pair of foundations on random heterogeneous medium. The random soil properties of interest are the elastic modulus, and the Poisson ratio. The elastic modulus is modeled as a spatially random field by adopting the lognormal distribution, which enables analyzing its large variability. Because soil Poisson ratio is bounded in practice between two extreme values, its random field is obtained by using the Beta distribution. In this study, one proposes for the Beta field determination, a mapping technique on the probability distribution function diagram, by solving a non-linear equation. However, the mean and variance are unchanged through the mapping operation. Because the soil Poisson ratio is a positive parameter, one prefers to perform the mapping operation with the probability function of the lognormal distribution. Also, the proposed technique can be used for other bounded soil properties such as the porosity. In this paper, settlement and differential settlement statistics prediction are carried out using Monte Carlo simulations combined with deterministic finite element method (DFEM). A performed parametric study shows the following: (i) as the variability of the elastic modulus increases as settlement and differential settlement statistics are important, also, settlement statistics decreases as the Poisson ratio variability increases, and differential settlement statistics do not seem be affected by its variability. (ii) settlement and differential settlement statistics are important for positive inter-property correlation. (iii) a great influence of the correlation lengths on settlement and differential settlement statistics. 相似文献
8.
A data driven multivariate adaptive regression splines (MARS) based algorithm for system reliability analysis of earth slopes having random soil properties under the framework of limit equilibrium method of slices is considered. The theoretical formulation is developed based on Spencer method (valid for general slip surfaces) satisfying all conditions of static equilibrium coupled with a nonlinear programming technique of optimization. Simulated noise is used to take account of inevitable modeling inaccuracies and epistemic uncertainties. The proposed MARS based algorithm is capable of achieving high level of computational efficiency in the system reliability analysis without significantly compromising the accuracy of results. 相似文献
9.
Strong wind and rainfall induced by extreme meteorological processes such as typhoons have a serious impact on the safety of bridges and offshore engineering structures. A new bivariate compound extreme value distribution is proposed to describe the probability dependency structure of annual extreme wind speed and concomitant process maximum rainfall intensity in typhoon-affected area. This probability model takes full account of the case that there may be no rainfall in a typhoon process. A case study based on the observation data of typhoon maximum wind speed and maximum rainfall intensity in Shanghai is conducted to testify the efficiency of the model. Weibull distributions with two parameters are applied to fit respective probability margins, and the joint probability distribution is constructed by Gumbel–Hougaard copula. The fitting results and K–S tests show that these models describe the original data well. The joint return periods are calculated by Poisson bivariate compound extreme value distribution we have proposed. They indicate that typhoons with no rain have smaller joint return periods, and wind speed is the main factor which impacts the change of the joint return periods. 相似文献
10.
This paper presents a novel probabilistic approach of random discrete element analysis (RDEA) to investigate the mechanism of rock fragmentation under uniaxial compression. This model combines the advantages of both random field theory and discrete element method in characterizing the spatial variation and uncertainty of microscopic material properties. The numerical results reveal that the stress-strain curves of a group of tests can match well the general trend of the experimental data, with the mean uniaxial compressive strength (UCS) of 10.18 MPa and the mean Young modulus of 1.73 GPa. The coefficient of variation (COV) for the rock samples is much lower than that of the initial random fields of particles because of the averaging effect of microscopic material property in obtaining the bulk values. The rock fragmentation is initiated by the breakage of weak particles within the rock mass, and it develops rapidly as the vertical loading stress approaches the UCS. The final damage zone resides dominantly in the weak region of the rock sample, and the distribution of material property coefficients follows a similar beta distribution as the corresponding initial random field. Rock samples with persistent “pillar-like” structures of strong particles can effectively resist the normal compression, resulting in high rock strengths. The traditional DEM simulation with a set of constant material properties can only represent one extreme realization of random field, which could significantly overestimate the rock strength. The proposed RDEA approach can effectively capture the uncertainty and complex interactions of rock fragmentation in a more realistic and reliable way. 相似文献
11.
《地学前缘(英文版)》2023,14(3):101541
In this study, the future landslide population amount risk (LPAR) is assessed based on integrated machine learning models (MLMs) and scenario simulation techniques in Shuicheng County, China. Firstly, multiple MLMs were selected and hyperparameters were optimized, and the generated 11 models were cross-integrated to select the best model to calculate landslide susceptibility; by calculating precipitation for different extreme precipitation recurrence periods and combining the susceptibility results to assess the landslide hazard. Using the town as the basic unit, the exposure and vulnerability of the future landslide population under different Shared Socioeconomic Pathways (SSPs) scenarios in each town were assessed, and then combined with the hazard to estimate the LPAR in 2050. The results showed that the integrated model with the optimized random forest model as the combination strategy had the best comprehensive performance in susceptibility assessment. The distribution of hazard classes is similar to susceptibility, and with an increase in precipitation, the low-hazard area and high-hazard decrease and shift to medium-hazard and very high-hazard classes. The high-risk areas for future landslide populations in Shuicheng County are mainly concentrated in the three southwestern towns with high vulnerability, whereas the northern towns of Baohua and Qinglin are at the lowest risk class. The LPAR increased with the intensity of extreme precipitation. The LPAR differs significantly among the SSPs scenarios, with the lowest in the “fossil-fueled development (SSP5)” scenario and the highest in the “regional rivalry (SSP3)” scenario. In summary, the landslide susceptibility model based on integrated machine learning proposed in this study has a high predictive capability. The results of future LPAR assessment can provide theoretical guidance for relevant departments to cope with future socioeconomic development challenges and make corresponding disaster prevention and mitigation plans to prevent landslide risks from a developmental perspective. 相似文献
12.
Summary Probabilistic analysis of random anisotropic damage mechanics problems is proposed in Parts of I and II. In Part I, based on the measured characteristics of random crack distribution on the surface of a rock specimen, a probabilistic law of damage variables for rock mass was presented as a Beta distribution by using the Monte-Carlo statistical simulation method. In part II, statistical estimation of a damage state and properties of random damaged rock mass are evaluated by Rosenblueth's point estimate method. Two stability problems involving randomly damaged rock mass have been analyzed using the finite element method, to illustrate the statistical estimation method. 相似文献
13.
Estuarine ecosystems provide many services to humans, but these ecosystems are also under pressure from human development, which has led to large investments in habitat protection and restoration. Restoration in estuaries is typically focused on emergent and submerged vegetation with the goal of achieving target areal coverage based on historic conditions. Such restoration targets assume no spatial heterogeneity in habitat value and bypass the functional target of restoring or maintaining delivery of ecosystem goods and services (EGS). We have developed a spatially explicit individual-based behavioral model intended to explore the functional role of habitat restoration on EGS delivery in an index system (Tampa Bay, FL) and for an index EGS (recreational fishing). Model scenarios are based on interaction of inter-annual differences in salinity/temperature patterns (wet, dry, average) with hindcasted “increases” in coverage and distribution of seagrass. Model predictions indicated that the effect of seagrass restoration to historic (1950s) levels on both fish and fishery production is dependent on salinity and temperature. This dependence is based on predicted fish response both to habitat changes and the effective spatial scale of different habitat components. Overall, average salinity/temperature conditions facilitated the highest positive functional response to seagrass restoration with extreme wet/dry years yielding lower or even negative functional responses, but these responses were localized and not homogenous about the estuary. The results of this study provide a methodology for using functional targets in restoration planning and highlight the importance of considering the entire habitat mosaic in valuing restored habitat from an EGS perspective. 相似文献
14.
This paper studies the probability distribution for the mobilised shear strength of a spatially variable soil mass that is subjected to a uniform stress state. Based on the mechanisms identified in two previous studies conducted by the authors, this study further proposes a probability distribution model for the mobilised shear strength that is based on the extreme value of normal random variables. It is concluded that the probability distribution of the mobilised shear strength of a spatially variable soil mass is affected by the line averaging effect along the potential slip plane and the number of independent potential slip planes. These two factors depend on the stress state and the orientation of the potential slip planes. With this model, the mobilised shear strength of a spatially variable soil mass can be simulated without the need of conducting random-field finite-element analyses. In addition, the strength characteristic value that is the 5% quantile in the Eurocodes can be easily derived from this model. 相似文献
15.
A test of transferability for landslides susceptibility models under extreme climatic events: application to the Messina 2009 disaster 总被引：2，自引：1，他引：1
A model building strategy is tested to assess the susceptibility for extreme climatic events driven shallow landslides. In fact, extreme climatic inputs such as storms typically are very local phenomena in the Mediterranean areas, so that with the exception of recently stricken areas, the landslide inventories which are required to train any stochastic model are actually unavailable. A solution is here proposed, consisting in training a susceptibility model in a source catchment, which was implemented by applying the binary logistic regression technique, and exporting its predicting function (selected predictors regressed coefficients) in a target catchment to predict its landslide distribution. To test the method, we exploit the disaster that occurred in the Messina area (southern Italy) on 1 October 2009 where, following a 250-mm/8-h storm, approximately two thousand debris flow/debris avalanches landslides in an area of 21 km2 triggered, killing 37 people and injuring more than 100, and causing 0.5 M € worth of structural damage. The debris flows and debris avalanches phenomena involved the thin weathered mantle of the Varisican low to high-grade metamorphic rocks that outcrop in the eastern slopes of the Peloritani Mounts. Two 10-km2-wide stream catchments, which are located inside the storm core area, were exploited: susceptibility models trained in the Briga catchment were tested when exported to predict the landslides distribution in the Giampilieri catchment. The prediction performance (based on goodness of fit, prediction skill, accuracy and precision assessment) of the exported model was then compared with that of a model prepared in the Giampilieri catchment exploiting its landslide inventory. The results demonstrate that the landslide scenario observed in the Giampilieri catchment can be predicted with the same high performance without knowing its landslide distribution: we obtained, in fact, a very poor decrease in predictive performance when comparing the exported model to the native random partition-based model. 相似文献
16.
Wang Jianfeng 《中国地质大学学报(英文版)》1998,9(2):2
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17.
The effect of undersampling on estimating the size of extreme natural hazards from historical data is examined. Tests using synthetic catalogs indicate that the tail of an empirical size distribution sampled from a pure Pareto probability distribution can range from having one-to-several unusually large events to appearing depleted, relative to the parent distribution. Both of these effects are artifacts caused by limited catalog length. It is more difficult to diagnose the artificially depleted empirical distributions, since one expects that a pure Pareto distribution is physically limited in some way. Using maximum-likelihood methods and the method of moments, we estimate the power-law exponent and the corner size parameter of tapered Pareto distributions for several natural hazard examples: tsunamis, floods, and earthquakes. Each of these examples has varying catalog lengths and measurement thresholds, relative to the largest event sizes. In many cases where there are only several orders of magnitude between the measurement threshold and the largest events, joint two-parameter estimation techniques are necessary to account for estimation dependence between the power-law scaling exponent and the corner size parameter. Results indicate that whereas the corner size parameter of a tapered Pareto distribution can be estimated, its upper confidence bound cannot be determined and the estimate itself is often unstable with time. Correspondingly, one cannot statistically reject a pure Pareto null hypothesis using natural hazard catalog data. Although physical limits to the hazard source size and attenuation mechanisms from source to site constrain the maximum hazard size, historical data alone often cannot reliably determine the corner size parameter. Probabilistic assessments incorporating theoretical constraints on source size and propagation effects are preferred over deterministic assessments of extreme natural hazards based on historical data. 相似文献
18.
A theory is proposed to evaluate the loosening earth pressure (vertical earth pressure after excavation) acting on a shallow tunnel in unsaturated ground with an arbitrary groundwater level. The theory is developed based on the limit equilibrium theory, combining soil–water characteristic curves, Mohr–Coulomb failure criteria, and effective stress for unsaturated soils. The proposed theory is applied to predict the vertical distribution of loosening earth pressure in unsaturated ground, which shows a significant difference from that in saturated ground. In unsaturated ground, suction contributes to the increase in effective loosening earth pressure and shear resistance. The remarkable effects of groundwater depth, soil type, and scale of overburden height and trapdoor width on loosening earth pressure are also revealed. Based on the soil–water characteristic curve, the degree of saturation decreases, which causes wet density to decrease and the total and effective loosening earth pressures to have contrary tendencies. Moreover, effective loosening earth pressures vary with soil type as the degree of saturation varies. The total loosening earth pressures are, however, very similar regardless of soil type, because wet density and shear resistance have similar tendencies. The proposed theory provides a valid model for loosening earth pressure in unsaturated ground that will be useful for shallow tunnel excavations. 相似文献
19.
基于饱和渗透系数空间变异结构的斜坡渗流及失稳特征 总被引：1，自引：0，他引：1
以往研究一般采用单随机变量方法（SRV）或基于水平或垂直方向波动范围生成的空间变异随机场来模拟岩土参数的空间变异性,对具有倾斜定向特征的空间变异随机场未有涉及.基于条件模拟相关理论和非侵入式随机有限元的理论框架,提出了利用序贯高斯模拟方法进行斜坡参数条件随机场模拟并运用有限元方法进行斜坡渗流和稳定性分析的方法.针对理想边坡,对各向同性和几何各向异性的共7种空间变异结构的饱和渗透系数（Ks）各进行了200次条件随机场模拟,基于条件随机场模拟结果进行了有限元渗流和稳定性计算,对每种空间变异结构多次计算结果进行了统计分析.结果表明:本文所提出的方法不仅再现了研究区域参数的空间二阶统计特性,通过设定变异函数参数进行不同空间变异类型、变异程度、变异定向性的随机场模拟,同时利用现场观测数据对随机场模拟结果进行条件限制,从而提高了随机场的赋值精度;Ks的空间变异结构对孔隙水压力的分布规律、地下水位线变化范围、稳定性系数和最危险滑动面分布特征均有一定程度的影响.本研究为库岸斜坡稳定性评价提供方法支撑. 相似文献
20.
The variability in seasonal mean and extreme precipitation is analyzed for several regions of Argentina to the north of 39º S, using long-term monthly time series data which expand from 1860 to 2006. The selected locations can be considered as representative of different climatic regions. This work focuses on the analysis of monthly rainfall distribution, significant seasonal trends, changes in variance and extreme monthly values, in order to establish the magnitude of the seasonal climatic rainfall variability through time for central Argentina. A 40-yr moving window was employed in order to analyze seasonal variability of rainfall extremes. Extremes were computed for different probability levels of a theoretical distribution function over/below the 80th/20th percentile. The gamma distribution was selected among five other theoretical distributions, and the scale and shape parameters were computed using the maximum likelihood estimation (MLE) and the bootstrap method for 1000 resample data sets, as well. Trend analysis was performed for each window on winter and summer means and tested for significance. The use of a moving window allowed detecting the window of maximum absolute values for the trends. Research results show significant temporal shifts in seasonal rainfall distribution and return values (RV) that were computed for different frequencies (once every five, 10 and 20 years). Generally, summer precipitation extremes have become wetter for the whole region. Rainfall amounts for summer wet/dry extremes (W/D) corresponding to the 90th (for W) and 10th (for D) percentiles were subjected to significant increase, but depending on the geographical area this effect spreads slightly differently over records of years. A common-for-all-stations period of such summer increase trend in extreme values spans from the window 1921-1960 to the last window analyzed: 1967-2006. This behavior was not observed for north and west Argentina during winter, except for the region represented by Bahía Blanca, where the 10% D extreme has increased throughout the study period. 相似文献