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1.
The knowledge of the high intensity tails of probability distributions that determine the rate of occurrence of extreme events of solar energetic particles is a critical element in the evaluation of hazards for human and robotic space missions. Here instead of the standard approach based on fitting a selected distribution function to the observed data we investigate a different approach, which is based on a study of the scaling properties of the maximum particle flux in time intervals of increasing length. To find the tail of the probability distributions we apply the “Max-Spectrum” method (Stoev, S.A., Michailidis, G., 2006. On the estimation of the heavy-tail exponent in time series using the Max-Spectrum. Technical Report 447, Department of Statistics, University of Michigan) to 1973–1997 IMP-8 proton data and the 1987–2008 GOES data, which cover a wide range of proton energies. We find that both data sets indicate a power-law tail with the power exponents close to 0.6 at least in the energy range 9–60 MeV. The underlying probability distribution is consistent with the Fréchet type (power-law behavior) extreme value distribution. Since the production of high fluxes of energetic particles is caused by fast Coronal Mass Ejections (CMEs) this heavy-tailed distribution also means that the Sun generates more fast CMEs than would be expected from a Poissonian-type process. 相似文献
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Hyun-Han Kwon Young-Il Moon 《Stochastic Environmental Research and Risk Assessment (SERRA)》2006,20(4):223-237
Hydrologic risk analysis for dam safety relies on a series of probabilistic analyses of rainfall-runoff and flow routing models, and their associated inputs. This is a complex problem in that the probability distributions of multiple independent and derived random variables need to be estimated in order to evaluate the probability of dam overtopping. Typically, parametric density estimation methods have been applied in this setting, and the exhaustive Monte Carlo simulation (MCS) of models is used to derive some of the distributions. Often, the distributions used to model some of the random variables are inappropriate relative to the expected behaviour of these variables, and as a result, simulations of the system can lead to unrealistic values of extreme rainfall or water surface levels and hence of the probability of dam overtopping. In this paper, three major innovations are introduced to address this situation. The first is the use of nonparametric probability density estimation methods for selected variables, the second is the use of Latin Hypercube sampling to improve the efficiency of MCS driven by the multiple random variables, and the third is the use of Bootstrap resampling to determine initial water surface level. An application to the Soyang Dam in South Korea illustrates how the traditional parametric approach can lead to potentially unrealistic estimates of dam safety, while the proposed approach provides rather reasonable estimates and an assessment of their sensitivity to key parameters. 相似文献
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J. T. Shiau 《Stochastic Environmental Research and Risk Assessment (SERRA)》2003,17(1-2):42-57
Extreme hydrological events are inevitable and stochastic in nature. Characterized by multiple properties, the multivariate
distribution is a better approach to represent this complex phenomenon than the univariate frequency analysis. However, it
requires considerably more data and more sophisticated mathematical analysis. Therefore, a bivariate distribution is the most
common method for modeling these extreme events. The return periods for a bivariate distribution can be defined using either
separate single random variables or two joint random variables. In the latter case, the return periods can be defined using
one random variable equaling or exceeding a certain magnitude and/or another random variable equaling or exceeding another
magnitude or the conditional return periods of one random variable given another random variable equaling or exceeding a certain
magnitude. In this study, the bivariate extreme value distribution with the Gumbel marginal distributions is used to model
extreme flood events characterized by flood volume and flood peak. The proposed methodology is applied to the recorded daily
streamflow from Ichu of the Pachang River located in Southern Taiwan. The results show a good agreement between the theoretical
models and observed flood data.
The author wishes to thank the two anonymous reviewers for their constructive comments that improving the quality of this
work. 相似文献
4.
Monica Riva Shlomo P. Neuman Alberto Guadagnini 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(1):195-207
Earth and environmental variables are commonly taken to have multivariate Gaussian or heavy-tailed distributions in space and/or time. This is based on the observation that univariate frequency distributions of corresponding samples appear to be Gaussian or heavy-tailed. Of particular interest to us is the well-documented but heretofore little noticed and unexplained phenomenon that whereas the frequency distribution of log permeability data often seems to be Gaussian, that of corresponding increments tends to exhibit heavy tails. The tails decay as powers of ? $ \alpha $ where 1 < $ \alpha $ < 2 is either constant or grows monotonically toward an asymptote with increasing separation distance or lag. We illustrate the latter phenomenon on 1-m scale log air permeabilities from pneumatic tests in 6 vertical and inclined boreholes completed in unsaturated fractured tuff near Superior, Arizona. We then show theoretically and demonstrate numerically, on synthetically generated signals, that whereas the case of constant $ \alpha $ is consistent with a collection of samples from truncated sub-Gaussian fractional Lévy noise, a random field (or process) subordinated to truncated fractional Gaussian noise, the case of variable $ \alpha $ is consistent with a collection of samples from truncated sub-Gaussian fractional Lévy motion (tfLm), a random field subordinated to truncated fractional Brownian motion. Whereas the first type of signal is relatively regular and characterized by Lévy index $ \alpha $ , the second is highly irregular (punctuated by spurious spikes) and characterized by the asymptote of $ \alpha $ values associated with its increments. We describe a procedure to estimate the parameters of univariate distributions characterizing such signals and apply it to our log air permeability data. The latter are found to be consistent with a collection of samples from tfLm with $ \alpha $ slightly smaller than 2, which is easily confused with a Gaussian field (characterized by constant $ \alpha $ = 2). The irregular (spiky) nature of this signal is typical of observed fractured rock properties. We propose that distributions of earth and environmental variable be inferred jointly from measured values and their increments in a way that insures consistency between these two sets of data. 相似文献
5.
We present theoretical tools from statistical physics for the calculation of non-Gaussian moments. In particular, we focus on the variational approximation and the cumulant expansion. These methods enable approximate but explicit moment calculations with non-Gaussian probability density functions (pdfs). Their use is illustrated by calculating the variance and the excess kurtosis for a univariate non-Gaussian pdf. We comment on the potential application of these methods in estimating the parameters of the recently proposed Spartan spatial random fields. 相似文献
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Starting from a recent paper by Murshed (Stoch Environ Res Risk Assess 25:897–911, 2011) in which a good performance of the Beta-k distribution in analyzing extreme hydrologic events is shown, in this paper, we propose the use of two new four-parameters distribution functions strongly related to the Beta-k distribution, namely the Beta-Dagum and the Beta-Singh-Maddala distributions. More in detail, the new distributions are a generalization of a reparametrization of Beta-k and Beta-p distributions, respectively. For these distributions some particular interpretations in terms of maximum and minimum of sequences of random variables can be derived and the maximal and minimal domain of attraction can be obtained. Moreover, the method of maximum likelihood, the method of moments and the method of L-moments are examined to estimate the parameters. Finally, two different applications on real data regarding maxima and minima of river flows are reported, in order to show the potentiality of these two models in the extreme events analysis. 相似文献
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Highly detailed physically based groundwater models are often applied to make predictions of system states under unknown forcing. The required analysis of uncertainty is often unfeasible due to the high computational demand. We combine two possible solution strategies: (1) the use of faster surrogate models; and (2) a robust data worth analysis combining quick first-order second-moment uncertainty quantification with null-space Monte Carlo techniques to account for parametric uncertainty. A structurally and parametrically simplified model and a proper orthogonal decomposition (POD) surrogate are investigated. Data worth estimations by both surrogates are compared against estimates by a complex MODFLOW benchmark model of an aquifer in New Zealand. Data worth is defined as the change in post-calibration predictive uncertainty of groundwater head, river-groundwater exchange flux, and drain flux data, compared to the calibrated model. It incorporates existing observations, potential new measurements of system states (“additional” data) as well as knowledge of model parameters (“parametric” data). The data worth analysis is extended to account for non-uniqueness of model parameters by null-space Monte Carlo sampling. Data worth estimates of the surrogates and the benchmark suggest good agreement for both surrogates in estimating worth of existing data. The structural simplification surrogate only partially reproduces the worth of “additional” data and is unable to estimate “parametric” data, while the POD model is in agreement with the complex benchmark for both “additional” and “parametric” data. The variance of the POD data worth estimates suggests the need to account for parameter non-uniqueness, like presented here, for robust results. 相似文献
10.
在地震子波非因果、混合相位的假设下,本文应用自回归滑动平均(ARMA)模型对地震子波进行参数化建模,并提出利用线性(矩阵方程法)和非线性(ARMA拟合方法)相结合的参数估计方式对该模型进行参数估计.在利用矩阵方程法确定模型参数范围的基础上,利用累积量拟合法精确估计参数.理论分析和仿真结果表明,该方式有较好的适应性：一方面提高了子波估计精度,避免单独使用矩阵方程法在短数据地震记录情况下可能带来的估计误差;另一方面提高了子波提取运算效率,降低了ARMA模型拟合方法参数范围确定的复杂性,避免了单纯使用滑动平均（MA）模型拟合法估计过多参数所导致的运算规模过大问题.初步应用结果表明该方法是有效可行的. 相似文献
11.
Investigation on the properties of the relationship between rare and extreme rainfall and flood volumes, under some distributional restrictions 总被引：1，自引：1，他引：0
Mauro Naghettini Nebai Tavares Gontijo Maria Manuela Portela 《Stochastic Environmental Research and Risk Assessment (SERRA)》2012,26(6):859-872
The fact that rainfall data are usually more abundant and more readily regionalized than streamflow data has motivated hydrologists to conceive methods that incorporate the hydrometeorologial information into flood frequency analyses. Some of them, particularly those derived from the French GRADEX method, involve assumptions concerning the relationship between extreme rainfall and flood volumes, under some distributional restrictions. In particular, for rainfall probability distributions exhibiting exponential-like upper tails, it is possible to derive the shape and scale of the probability distribution of flood volumes by hypothesizing the basic properties of such a relationship, under rare and/or extreme conditions. This paper focuses on a parametric mathematical model for the relationship between rare and extreme rainfall and flood volumes under exponentially-tailed distributions. The model is analyzed and fitted to rare and extreme events derived from hydrological simulation of long stochastically-generated synthetic series of rainfall and evaporation for the Indaiá River basin, located in south-central Brazil. The paper also provides a sensitivity analysis of the model parameters in order to better understand flood events under rare and extreme conditions. By working with hydrologically plausible hypothetical events, the modeling approach proved to be a useful way to explore extraordinary rainfall and flood events. The results from this exploratory analysis provide grounds to derive some conclusions regarding the relative positions of the upper tails of the probability distributions of rainfall and flood volumes. 相似文献
12.
Random variable simulation has been applied to many applications in hydrological modelling, flood risk analysis, environmental impact assessment, etc. However, computer codes for simulation of distributions commonly used in hydrological frequency analysis are not available in most software libraries. This paper presents a frequency‐factor‐based method for random number generation of five distributions (normal, log–normal, extreme‐value type I, Pearson type III and log‐Pearson type III) commonly used in hydrological frequency analysis. The proposed method is shown to produce random numbers of desired distributions through three means of validation: (1) graphical comparison of cumulative distribution functions (CDFs) and empirical CDFs derived from generated data; (2) properties of estimated parameters; (3) type I error of goodness‐of‐fit test. An advantage of the method is that it does not require CDF inversion, and frequency factors of the five commonly used distributions involves only the standard normal deviate. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
13.
D. E. Villalta L. Bravo de Guenni A. M. Sajo-Castelli 《Stochastic Environmental Research and Risk Assessment (SERRA)》2020,34(3):513-529
Extreme environmental events have considerable impacts on society.
Preparation to mitigate or forecast accurately these events is a growing concern for governments. In this regard, policy and decision makers require accurate tools for risk estimation in order to take informed decisions. This work proposes a Bayesian framework for a unified treatment and statistical modeling of the main components of risk: hazard, vulnerability and exposure. Risk is defined as the expected economic loss or population affected as a consequence of a hazard event. The vulnerability is interpreted as the loss experienced by an exposed population due to hazard events. The framework combines data of different spatial and temporal supports. It produces a sequence of temporal risk maps for the domain of interest including a measure of uncertainty for the hazard and vulnerability. In particular, the considered hazard (rainfall) is interpolated from point-based measured rainfall data using a hierarchical spatio-temporal Kriging model, whose parameters are estimated using the Bayesian paradigm. Vulnerability is modeled using zero-inflated distributions with parameters dependent on climatic variables at local and large scales. Exposure is defined as the total population settled in the spatial domain and is interpolated using census data. The proposed methodology was applied to the Vargas state of Venezuela to map the spatio-temporal risk for the period 1970–2006. The framework highlights both high and low risk areas given extreme rainfall events. 相似文献
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— Analytical expressions to predict the enhancement of permeability due to stress-induced microcracking in initially low porosity rock are presented. A fracture mechanical microcrack model is employed to derive integrated effective hydraulic variables as a function of stress, which are then used to calculate the evolution of permeability using the statistically-based Dienes model. The model enables determination of permeability enhancement as a function of two loading parameters and three material parameters. Results are in reasonable agreement with experimental measurements and indicate that appreciable increases in permeability can be anticipated during brittle failure. The analytical nature of the model makes it easily incorporatable into numerical models that require quantification of the permeability evolution as a function of stress, for which there is currently no law. 相似文献
18.
ABSTRACTFlood quantile estimation based on partial duration series (peak over threshold, POT) represents a noteworthy alternative to the classical annual maximum approach since it enlarges the available information spectrum. Here the POT approach is discussed with reference to its benefits in increasing the robustness of flood quantile estimations. The classical POT approach is based on a Poisson distribution for the annual number of exceedences, although this can be questionable in some cases. Therefore, the Poisson distribution is compared with two other distributions (binomial and Gumbel-Schelling). The results show that only rarely is there a difference from the Poisson distribution. In the second part we investigate the robustness of flood quantiles derived from different approaches in the sense of their temporal stability against the occurrence of extreme events. Besides the classical approach using annual maxima series (AMS) with the generalized extreme value distribution and different parameter estimation methods, two different applications of POT are tested. Both are based on monthly maxima above a threshold, but one also uses trimmed L-moments (TL-moments). It is shown how quantile estimations based on this “robust” POT approach (rPOT) become more robust than AMS-based methods, even in the case of occasional extraordinary extreme events.
Editor M.C. Acreman Associate editor A. Viglione 相似文献
19.
Parametric uncertainty assessment of hydrological models: coupling UNEEC-P and a fuzzy general regression neural network 总被引：1，自引：1，他引：0
Due to the complicated nature of environmental processes, consideration of uncertainty is an important part of environmental modelling. In this paper, a new variant of the machine learning-based method for residual estimation and parametric model uncertainty is presented. This method is based on the UNEEC-P (UNcertainty Estimation based on local Errors and Clustering – Parameter) method, but instead of multilayer perceptron uses a “fuzzified” version of the general regression neural network (GRNN). Two hydrological models are chosen and the proposed method is used to evaluate their parametric uncertainty. The approach can be classified as a hybrid uncertainty estimation method, and is compared to the group method of data handling (GMDH) and ordinary kriging with linear external drift (OKLED) methods. It is shown that, in terms of inherent complexity, measured by Akaike information criterion (AIC), the proposed fuzzy GRNN method has advantages over other techniques, while its accuracy is comparable. Statistical metrics on verification datasets demonstrate the capability and appropriate efficiency of the proposed method to estimate the uncertainty of environmental models. 相似文献
20.
Abstract This study examines relationships between model parameters and urbanization variables for evaluating urbanization effects in a watershed. Rainfall–runoff simulation using the Nash model is the main basis of the study. Mean rainfall and excesses resulting from time-variant losses were completed using the kriging and nonlinear programming methods, respectively. Calibrated parameters of 47 events were related to urbanized variables, change of shape parameter responds more sensitively than that of scale parameter based on comparisons between annual average and optimal interval methods. Regression equations were used to obtain four continuous correlations for linking shape parameter with urbanization variables. Verification of 10 events demonstrates that shape parameter responds more strongly to imperviousness than to population, and a power relationship is suitable. Therefore, an imperviousness variable is a major reference for analysing urbanization changes to a watershed. This study found that time to peak of IUH was reduced from 11.76 to 3.97 h, whereas peak discharge increased from 44.79 to 74.92 m3/s. Editor D. Koutsoyiannis; Associate editor S. Grimaldi Citation Huang, S.-Y., Cheng, S.-J., Wen, J.-C. and Lee, J.-H., 2012. Identifying hydrograph parameters and their relationships to urbanization variables. Hydrological Sciences Journal, 57 (1), 144–161. 相似文献