气候变化领域集成服务门户(CCPortal): Ensemble modeling of stochastic unsteady open-channel flow in terms of its time-space evolutionary probability distribution

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DOI	10.5194/hess-22-2007-2018
	Ensemble modeling of stochastic unsteady open-channel flow in terms of its time-space evolutionary probability distribution - Part 2: Numerical application
	Dib A.; Kavvas M.L.
发表日期	2018
ISSN	1027-5606
起始页码	2007
结束页码	2021
卷号	22 期号:3
英文摘要	The characteristic form of the Saint-Venant equations is solved in a stochastic setting by using a newly proposed Fokker-Planck Equation (FPE) methodology. This methodology computes the ensemble behavior and variability of the unsteady flow in open channels by directly solving for the flow variables' time-space evolutionary probability distribution. The new methodology is tested on a stochastic unsteady open-channel flow problem, with an uncertainty arising from the channel's roughness coefficient. The computed statistical descriptions of the flow variables are compared to the results obtained through Monte Carlo (MC) simulations in order to evaluate the performance of the FPE methodology. The comparisons show that the proposed methodology can adequately predict the results of the considered stochastic flow problem, including the ensemble averages, variances, and probability density functions in time and space. Unlike the large number of simulations performed by the MC approach, only one simulation is required by the FPE methodology. Moreover, the total computational time of the FPE methodology is smaller than that of the MC approach, which could prove to be a particularly crucial advantage in systems with a large number of uncertain parameters. As such, the results obtained in this study indicate that the proposed FPE methodology is a powerful and time-efficient approach for predicting the ensemble average and variance behavior, in both space and time, for an open-channel flow process under an uncertain roughness coefficient. © Author(s) 2018.
语种	英语
scopus关键词	Fokker Planck equation; Monte Carlo methods; Probability density function; Probability distributions; Stochastic systems; Uncertainty analysis; Computational time; Numerical applications; Roughness coefficient; Saint Venant equation; Statistical descriptions; Stochastic settings; Uncertain parameters; Unsteady open channel flows; Open channel flow; methodology; modeling; Monte Carlo analysis; numerical method; numerical model; open channel flow; parameter estimation; probability; simulation; spatiotemporal analysis; statistical analysis; unsteady flow
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/160070
作者单位	Dib, A., Department of Civil and Environmental Engineering, University of California, Davis, CA 95616, United States; Kavvas, M.L., Department of Civil and Environmental Engineering, University of California, Davis, CA 95616, United States
推荐引用方式 GB/T 7714	Dib A.,Kavvas M.L.. Ensemble modeling of stochastic unsteady open-channel flow in terms of its time-space evolutionary probability distribution - Part 2: Numerical application[J],2018,22(3).
APA	Dib A.,&Kavvas M.L..(2018).Ensemble modeling of stochastic unsteady open-channel flow in terms of its time-space evolutionary probability distribution - Part 2: Numerical application.Hydrology and Earth System Sciences,22(3).
MLA	Dib A.,et al."Ensemble modeling of stochastic unsteady open-channel flow in terms of its time-space evolutionary probability distribution - Part 2: Numerical application".Hydrology and Earth System Sciences 22.3(2018).