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1.
基于概率统计的甚宽频带地震计自噪声水平分析 总被引：1，自引：1，他引：0
使用连续1000hr的数据计算甚宽频带地震计自噪声,应用概率统计方法对计算结果进行分析,分别以单小时结果众值、单频点概率统计及分频带概率统计等3种表达方式对分析结果进行展示。通过比较分析,发现第1种方式便于异常结果溯源,但无法获取自噪声非均匀分布特征;第2种方式可以获取固定频点上自噪声水平非均匀分布的详细特征,但高概率值呈现条带分布,没有明显量级差异;第3种方式得到了对应于中心频点的且具有量级差异的高概率值,为地震计自噪声的数学数值建模提供了支持。在异常数据数量较少的情况下,异常结果在后2种方式中得不到体现。 相似文献
2.
Abstract One of the basic tasks in geomorphologic analysis is to know the probability distributions of the stream lengths of different orders. In practical applications, this information is useful for basin rainfall-runoff modelling. The objective of this study is to determine the length distributions of the Strahler streams. A Poisson process was used to derive the theoretical distributions. The result showed that the length distribution of the first-order stream is an exponential distribution and the second-order or higher order stream length is a gamma distribution. In order to verify the theoretical distributions, a digital elevation model (DEM) was adopted to calculate the stream lengths of four basins in Taiwan. Kolmogorov-Smirnov and chi-square tests were used to test the goodness-of-fit of the data. Results showed that the length distributions of the first- and second-order streams analysed by using DEM correspond with those from the derived distribution method. 相似文献
3.
S. K. Powar H. V. Kulkarni 《Stochastic Environmental Research and Risk Assessment (SERRA)》2015,29(6):1691-1708
The quantile of a probability distribution, known as return period or hydrological design value of a hydrological variable is the value corresponding to fixed non-exceedence probability and is very important notion in hydrology. In hydraulic engineering design and water resources management, confidence interval (CI) estimation for a population quantile is of primary interest and among other applications, is used to assess the pollution level of a contaminant in water, air etc. The accuracy on such estimation directly influences the engineering investments and safety. The two parameter Weibull, Pareto, Lognormal, Inverse Gaussian, Gamma are some commonly used probability models in such applications. In spite of its practical importance, the problem of CI estimation of a quantile of these widely applicable distributions has been less attended in the literature. In this paper, a new method is proposed to obtain a CI for a quantile of any distribution for which [or the probability distribution of any one-to-one function of the underlying random variable (RV)] generalized pivotal quantities (GPQs) exist for its parameters. The proposed method is elucidated by constructing CIs for quantiles of Weibull, Pareto, Lognormal, Extreme value distribution of type-I for minimum, Exponential and Normal distributions for complete as well as type II singly right censored samples. The empirical performance evaluation of the proposed method evinced that the proposed method has exact well concentrated coverage probabilities near the nominal level even for small uncensored samples as small as 5 and for censored samples as long as the proportion of censored observations is up to 0.70. The existing methods for Weibull distribution have poor or dispersed coverage probabilities with respect to the nominal level for complete samples. Applications of the proposed method in ground water monitoring and in the assessment of air pollution are illustrated for practitioners. 相似文献
4.
Computational aspects in use of entropy theory in predicting water quality levels at discontinued stations 总被引：1，自引：0，他引：1
A. Kusmulyono I. Goulter 《Stochastic Environmental Research and Risk Assessment (SERRA)》1995,9(3):215-237
The computational aspects of using a new, entropy-based, theory to predict water quality values at discontinued water quality monitoring stations are discussed. The main computational issues addressed are the level of discretization used in converting the continuous probability distribution of water quality values to the discrete levels required for the entropy function, and the choice of the interval of time for which to assign the value of the water quality (period of time averaging) through the entropy function. Unlike most cases of entropy applications involving discretization of continuous functions the results of using entropy theory to predict water quality values at discontinued monitoring stations in this application appear to be insensitive to the choice of the level of discretization even down to the very coarse level discretization associated with only eight intervals. However, depending on the length of record available the choice of the time interval for which the water quality values are assigned (period for time averaging) appear to have a significant impact on the accuracy of the results. 相似文献
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Lawrence D. Lemke Andrew S. Bahrou 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(1):27-39
Quantifying human cancer risk arising from exposure to contaminated groundwater is complicated by the many hydrogeological,
environmental, and toxicological uncertainties involved. In this study, we used Monte Carlo simulation to estimate cancer
risk associated with tetrachloroethene (PCE) dissolved in groundwater by linking three separate models for: (1) reactive contaminant
transport; (2) human exposure pathways; and (3) the PCE cancer potency factor. The hydrogeologic model incorporates an analytical
solution for a one-dimensional advective–dispersive–reactive transport equation to determine the PCE concentration in a water
supply well located at a fixed distance from a continuous source. The pathway model incorporates PCE exposure through ingestion,
inhalation, and dermal contact. The toxicological model combines epidemiological data from eight rodent bioassays of PCE exposure
in the form of a composite cumulative distribution frequency curve for the human PCE cancer potency factor. We assessed the
relative importance of individual model variables through their correlation with expected cancer risk calculated in an ensemble
of Monte Carlo simulations with 20,000 trials. For the scenarios evaluated, three factors were most highly correlated with
cancer risk: (1) the microbiological decay constant for PCE in groundwater, (2) the linear groundwater pore velocity, and
(3) the cancer potency factor. We then extended our analysis beyond conventional expected value risk assessment using the
partitioned multiobjective risk method (PMRM) to generate expected-value functions conditional to a 1 in 100,000 increased
cancer risk threshold. This approach accounts for low probability/high impact outcomes separately from the conventional unconditional
expected values. Thus, information on potential worst-case outcomes can be quantified for decision makers. Using PMRM, we
evaluated the cost-benefit relationship of implementing several postulated risk management alternatives intended to mitigate
the expected and conditional cancer risk. Our results emphasize the importance of hydrogeologic models in risk assessment,
but also illustrate the importance of integrating environmental and toxicological uncertainty. When coupled with the PMRM,
models integrating uncertainty in transport, exposure, and potency constitute an effective risk assessment tool for use within
a risk-based corrective action (RBCA) framework. 相似文献
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The soil-covered landscape surface can be idealized from two viewpoints. The intuitive view is of a smooth, absolutely continuous surface with continuous contour lines and measurable in integral dimensions. The alternative view emphasizes the roughness, a surface of little regularity and at the limit of no contours, the appropriate measure being that of fractional Hausdorff dimension. Regularity is a local property and both idealizations need to stop far short of the limit to avoid awkward consequences. The dichotomy of viewpoint can be matched in the theory of Gaussian random fields. These, if they are smooth, are very smooth but if they are irregular they are highly irregular (erratic); there is no middle ground. This Belayev dichotomy is defined and both modes applied to the soil-covered landscape. On the one hand, if the landscape is subject to a general diffusive type degradation or more generally a Davisian downwasting regime then the curvature of the landscape surface is progressively straightened and the distribution of gradient (increments) along a typical traverse will eventually adopt a Gaussian form. Then from the irregular viewpoint the surface is ultimately well represented by a fractional Brownian surface of low Hausdorff dimension (2·0 < dim < 2·3). The Hausdorff dimension is directly related to the entropy of the landscape and as degradation proceeds both quantities decrease in value. On the other hand, if the surface is regarded as smooth and well represented by an absolutely continuous Gaussian field then the mean value of the number of upcrossings of a level or the extent of an excursion set will also be Gaussian. This analysis is restricted to one dimension; the number of times a profile curve crosses or the amount of time it spends above any given level. Predictions from both viewpoints are substantially corroborated in a map analysis of 15 sites on varied terrains in Southern England and the map analysis checked against one based upon digital tape data for one of the sites. 相似文献
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A. Gnauck 《洁净——土壤、空气、水》1990,18(1):119-132
A water-quality-related assessment of the state of waters can be carried dout by the graphic or computer-aided fitting of probability functions of qualitative and quantitative characteristics of water quality. For this, five discrete and ten continuous distribution functions in potential fields of application of ecology and water quality management are represented. In evaluations of examples of measured data of two flowing waters there prove to be suitable as models above all the power normal distribution (chemical quantities), LN3-distribution (biochemically removable substances) and the Johnson distribution (physical measured quantities). Evaluations like that of stationary probability distributions of variables of water quality having been observed for many years at consecutive measuring stations of flowing waters lead to distribution patterns which can be used for optimizing measurement and investigation programs. 相似文献
11.
Kyung-Ho Kim Kang-Kun Lee 《Stochastic Environmental Research and Risk Assessment (SERRA)》2007,21(6):785-794
A new methodology is proposed to optimize monitoring networks for identification of the extent of contaminant plumes. The
optimal locations for monitoring wells are determined as the points where maximal decreases are expected in the quantified
uncertainty about contaminant existence after well installation. In this study, hydraulic conductivity is considered to be
the factor that causes uncertainty. The successive random addition (SRA) method is used to generate random fields of hydraulic
conductivity. The expected value of information criterion for the existence of a contaminant plume is evaluated based on how
much the uncertainty of plume distribution reduces with increases in the size of the monitoring network. The minimum array
of monitoring wells that yields the maximum information is selected as the optimal monitoring network. In order to quantify
the uncertainty of the plume distribution, the probability map of contaminant existence is made for all generated contaminant
plume realizations on the domain field. The uncertainty is defined as the sum of the areas where the probability of contaminant
existence or nonexistence is uncertain. Results of numerical experiments for determination of optimal monitoring networks
in heterogeneous conductivity fields are presented. 相似文献
12.
G. TSAKIRIS 《水文科学杂志》2013,58(5):437-447
Abstract The paper is concerned with the modelling of rainfall occurrence in continuous time. The Alternating Renewal Process is employed for the evaluation of probability distribution functions for total wet and dry periods over a homogeneous time interval (0, t). The derived general solution is simplified by assuming that the individual wet and dry intervals are random variables following an Erlang distribution, in particular an exponential distribution. Data on a continuous time scale from the Mikra Station in Greece are used to illustrate the proposed methodology. 相似文献
13.
Hossein Ebrahimian Fatemeh Jalayer Domenico Asprone Anna M. Lombardi Warner Marzocchi Andrea Prota Gaetano Manfredi 《地震工程与结构动力学》2014,43(14):2179-2197
Operative seismic aftershock risk forecasting can be particularly useful for rapid decision‐making in the presence of an ongoing sequence. In such a context, limit state first‐excursion probabilities (risk) for the forecasting interval (a day) can represent the potential for progressive state of damage in a structure. This work lays out a performance‐based framework for adaptive aftershock risk assessment in the immediate post‐mainshock environment. A time‐dependent structural performance variable is adopted in order to measure the cumulative damage in a structure. A set of event‐dependent fragility curves as a function of the first‐mode spectral acceleration for a prescribed limit state is calculated by employing back‐to‐back nonlinear dynamic analyses. An epidemic‐type aftershock sequence model is employed for estimating the spatio‐temporal evolution of aftershocks. The event‐dependent fragility curves for a given limit state are then integrated together with the probability distribution of aftershock spectral acceleration based on the epidemic‐type aftershock sequence aftershock hazard. The daily probability of limit state first‐excursion is finally calculated as a weighted combination of the sequence of limit state probabilities conditioned on the number of aftershocks. As a numerical example, daily aftershock risk is calculated for the L'Aquila 2009 aftershock sequence (central Italy). A representative three‐story reinforced concrete frame with infill panels, which has cyclic strength and stiffness degradation, is used in order to evaluate the progressive damage. It is observed that the proposed framework leads to a sound forecasting of limit state first‐excursion in the structure for two limit states of significant damage and near collapse. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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Ugo Moisello 《水文研究》2002,16(13):2667-2684
The maximum depth of a river section is schematized as a non‐stationary continuous‐parameter continuous stochastic process, with a three‐parameter lognormal distribution. Two processes, represented by a first‐order and a second‐order differential equation, are considered. Non‐stationarity is accounted for by the mean, the other parameters being assumed constant. The continuous processes are then discretized as AR(1) and ARMA(2,1) processes respectively, and used for computing the conditional probability (which is of practical interest) for a given maximum depth not to be exceeded in a period of given length. The models are applied to the River Po (Italy) and the AR(1) model is found to be preferable. An analysis of the effect of discretizing the parameter is also carried out, considering the second‐order model and the conditional probability, for which analytical results for the continuous‐parameter model are available. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
16.
Acceleration time histories of horizontal earthquake ground motion are obtained by inverting the discrete Fourier transform, which is defined by modelling the probability distribution of the Fourier phase differences conditional on the Fourier amplitude. The Fourier amplitude spectrum is modelled as a scaled, lognormal probability density function. Three parameters are necessary to define the Fourier amplitude spectrum. They are the total energy of the accelerogram, the central frequency, and the spectral bandwidth. The Fourier phase differences are simulated conditional on the Fourier amplitudes. The amplitudes are classified into three categories: small, intermediate and large. For each amplitude category, a beta distribution or a combination of a beta distribution and a uniform distribution are defined for the phase differences. Seven parameters are needed to completely define the phase difference distributions: two for each of the three beta distributions, and the weight of the uniform distribution for phase differences corresponding to small Fourier amplitudes. Approximately 300 uniformly processed horizontal ground motion records from recent California earthquakes are used to develop prediction formulas for the model parameters, as well as to validate the simulation model. The moment magnitude of the earthquakes ranges from 5.8 to 7.3. The source to site distance for all the records is less than 100 km. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
17.
在基于性能的抗震设计中,为了使结构在整个生命周期内费用达到最小,不仅需要确定各个性能水平的目标失效概率,同时还需要确定不同性能水平目标失效概率之间的合理关系。本文针对这个问题。研究了在结构造价一定的情况下,不同性能水平失效概率的合理比例关系,使得在设计基准期内结构损失达到最小。在本文中,根据我国建筑抗震设计规范的条件,仅考虑“小震不坏”和“大震不倒”两个性能水平。 相似文献
18.
A function for the bed-load sediment transport rate is derived. This function is obtained by using the entrainment probabilities of the rolling and lifted sediment grains, and by introducing two travel lengths, respectively. The predictions from the new bed-load function agree well with experimental results over the entire experimental range and show significant improvement over the commonly used formula for the bed-load transport rate. The new function shows that, in terms of contributing to the bed-load transport rate, the total entrainment probability of the sediment grains is a weighted summation of those for the lifted and rolling grains, rather than a simple addition of the two. The function is also used to predict the total entrainment probability, saltation length, and the bed layer thickness at a high bed-load transport rate. These predictions all agree well with the experimental results. It is found that, on average, the travel length for the rolling sand grains is about an order of magnitude less than that of the lifted grains. 相似文献
19.
A. Chaudhuri M. Sekhar 《Stochastic Environmental Research and Risk Assessment (SERRA)》2006,21(2):159-173
During probabilistic analysis of flow and transport in porous media, the uncertainty due to spatial heterogeneity of governing parameters are often taken into account. The randomness in the source conditions also play a major role on the stochastic behavior in distribution of the dependent variable. The present paper is focused on studying the effect of both uncertainty in the governing system parameters as well as the input source conditions. Under such circumstances, a method is proposed which combines with stochastic finite element method (SFEM) and is illustrated for probabilistic analysis of concentration distribution in a 3-D heterogeneous porous media under the influence of random source condition. In the first step SFEM used for probabilistic solution due to spatial heterogeneity of governing parameters for a unit source pulse. Further, the results from the unit source pulse case have been used for the analysis of multiple pulse case using the numerical convolution when the source condition is a random process. The source condition is modeled as a discrete release of random amount of masses at fixed intervals of time. The mean and standard deviation of concentration is compared for the deterministic and the stochastic system scenarios as well as for different values of system parameters. The effect of uncertainty of source condition is also demonstrated in terms of mean and standard deviation of concentration at various locations in the domain. 相似文献
20.
The continuous time random walk (CTRW) has both an elegant mathematical theory and a successful record at modeling solute transport in the subsurface. However, there are some interpretation ambiguities relating to the relationship between the discrete CTRW transition distributions and the underlying continuous movement of solute that have not been addressed in existing literature. These include the exact definition of “transition”, and the extent to which transition probability distributions are unique/quantifiable from data. Here, we present some theoretical results which address these uncertainties in systems with an advective bias. Simultaneously, we present an alternative, reduced parameter CTRW formulation for general advective transport in heterogeneous porous media, which models early- and late-time transport by use of random transition times between sparse, imaginary planes normal to flow. We show that even in the context of this reduced-parameter formulation there is nonuniqueness in the definitions of both transition lengths and waiting time distributions, and that neither may be uniquely determined from experimental data. For practical use of this formulation, we suggest Pareto transition time distributions, leading to a two-degree-of-freedom modeling approach. We then demonstrate the power of this approach in fitting two sets of existing experimental data. While the primary focus is the presentation of new results, the discussion is designed to be pedagogical and to provide a good entry point into practical modeling of solute transport with the CTRW. 相似文献