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Bivariate flood frequency analysis using the copula function: a case study of the Litija station on the Sava River 总被引:3,自引:0,他引:3 下载免费PDF全文
As an alternative to the commonly used univariate flood frequency analysis, copula frequency analysis can be used. In this study, 58 flood events at the Litija gauging station on the Sava River in Slovenia were analysed, selected based on annual maximum discharge values. Corresponding hydrograph volumes and durations were considered. Different bivariate copulas from three families were applied and compared using different statistical, graphical and upper tail dependence tests. The parameters of the copulas were estimated using the method of moments with the inversion of Kendall's tau. The Gumbel–Hougaard copula was selected as the most appropriate for the pair of peak discharge and hydrograph volume (Q‐V). The same copula was also selected for the pair hydrograph volume and duration (V‐D), and the Student‐t copula was selected for the pair of peak discharge and hydrograph duration (Q‐D). The differences among most of the applied copulas were not significant. Different primary, secondary and conditional return periods were calculated and compared, and some relationships among them were obtained. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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Assessment of climate change or climate variability is a significant topic in most geophysical disciplines. In this study, the flood frequency approach was selected to analyze changes in flood series. Discharge data from 55 gaging stations in Slovenia were used. The annual maximum method was applied to define the samples. The data sets were divided into 30-year periods based on a 10-year moving window. For each part of the data-set, the flood frequency analysis was performed. Changes in the estimated design discharge values with a 10-year return period, which is commonly used in engineering design, were observed for the two selected 30-year periods, namely 1961–1990 and 1981–2010, and the results were compared with the Mann–Kendall (MK) test. The results indicate that no uniform pattern can be found in the differences between estimated design discharge values for the two selected periods. The same applies to the MK trend test results, which were positive and statistically significant with the chosen significance level of 0.05 only for approximately 5% of stations. However, our comparison of the results of the flood frequency analyses among different 30-year periods showed considerable changes in the design discharge for some stations. 相似文献
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A priori testing of sparse adaptive polynomial chaos expansions using an ocean general circulation model database 总被引:1,自引:0,他引:1
Justin Winokur Patrick Conrad Ihab Sraj Omar Knio Ashwanth Srinivasan W. Carlisle Thacker Youssef Marzouk Mohamed Iskandarani 《Computational Geosciences》2013,17(6):899-911
This work explores the implementation of an adaptive strategy to design sparse ensembles of oceanic simulations suitable for constructing polynomial chaos surrogates. We use a recently developed pseudo-spectral algorithm that is based on a direct application of the Smolyak sparse grid formula and that allows the use of arbitrary admissible sparse grids. The adaptive algorithm is tested using an existing simulation database of the oceanic response to Hurricane Ivan in the Gulf of Mexico. The a priori tests demonstrate that sparse and adaptive pseudo-spectral constructions lead to substantial savings over isotropic sparse sampling in the present setting. 相似文献
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Alen Alexanderian Justin Winokur Ihab Sraj Ashwanth Srinivasan Mohamed Iskandarani William C. Thacker Omar M. Knio 《Computational Geosciences》2012,16(3):757-778
Polynomial chaos (PC) expansions are used to propagate parametric uncertainties in ocean global circulation model. The computations
focus on short-time, high-resolution simulations of the Gulf of Mexico, using the hybrid coordinate ocean model, with wind
stresses corresponding to hurricane Ivan. A sparse quadrature approach is used to determine the PC coefficients which provides
a detailed representation of the stochastic model response. The quality of the PC representation is first examined through
a systematic refinement of the number of resolution levels. The PC representation of the stochastic model response is then
utilized to compute distributions of quantities of interest (QoIs) and to analyze the local and global sensitivity of these
QoIs to uncertain parameters. Conclusions are finally drawn regarding limitations of local perturbations and variance-based
assessment and concerning potential application of the present methodology to inverse problems and to uncertainty management. 相似文献
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Ihab Sraj Kyle T. Mandli Omar M. Knio Clint N. Dawson Ibrahim Hoteit 《Ocean Dynamics》2017,67(12):1535-1551
An efficient method for inferring Manning’s n coefficients using water surface elevation data was presented in Sraj et al. (Ocean Modell 83:82–97 2014a) focusing on a test case based on data collected during the Tōhoku earthquake and tsunami. Polynomial chaos (PC) expansions were used to build an inexpensive surrogate for the numerical model GeoClaw, which were then used to perform a sensitivity analysis in addition to the inversion. In this paper, a new analysis is performed with the goal of inferring the fault slip distribution of the Tōhoku earthquake using a similar problem setup. The same approach to constructing the PC surrogate did not lead to a converging expansion; however, an alternative approach based on basis pursuit denoising was found to be suitable. Our result shows that the fault slip distribution can be inferred using water surface elevation data whereas the inferred values minimize the error between observations and the numerical model. The numerical approach and the resulting inversion are presented in this work. 相似文献
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ABSTRACTSuspended solids are present in every river, but high quantities can worsen the ecological conditions of streams; therefore, effective monitoring and analysis of this hydrological variable are necessary. Frequency, seasonality, inter-correlation, extreme events, trends and lag analyses were carried out for peaks of suspended sediment concentration (SSC) and discharge (Q) data from Slovenian streams using officially monitored data from 1955 to 2006 that were made available by the Slovenian Environment Agency. In total more than 500 station-years of daily Q and SSC data were used. No uniform (positive or negative) trend was found in the SSC series; however, all the statistically significant trends were decreasing. No generalization is possible for the best fit distribution function. A seasonality analysis showed that most of the SSC peaks occurred in the summer (short-term intense convective precipitation produced by thunderstorms) and in the autumn (prolonged frontal precipitation). Correlations between Q and SSC values were generally relatively small (Pearson correlation coefficient values from 0.05 to 0.59), which means that the often applied Q–SSC curves should be used with caution when estimating annual suspended sediment loads. On average, flood peak Q occurred after the corresponding SSC peak (clockwise-positive hysteresis loops), but the average lag time was rather small (less than 1 day).
Editor M.C. Acreman; Associate editor Y. Gyasi-Agyei 相似文献
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