DOI: 10.5194/hess-21-6541-2017
Scopus记录号: 2-s2.0-85039866192
论文题名: Development and evaluation of a stochastic daily rainfall model with long-term variability
作者: Chowdhury A ; F ; M ; K ; , Lockart N ; , Willgoose G ; , Kuczera G ; , Kiem A ; S ; , Manage N ; P
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 12 起始页码: 6541
结束页码: 6558
语种: 英语
Scopus关键词: Markov processes
; Probability distributions
; Stochastic models
; Stochastic systems
; Daily rainfall model
; Gamma distribution
; Long-term variability
; Mean and standard deviations
; Primary objective
; Stochastic rainfall generations
; Temporal resolution
; Transition probabilities
; Rain
; diurnal variation
; Markov chain
; model test
; parameter estimation
; parameterization
; precipitation assessment
; rainfall
; rainfall-runoff modeling
; resolution
; stochasticity
; valuation
英文摘要: The primary objective of this study is to develop a stochastic rainfall generation model that can match not only the short resolution (daily) variability but also the longer resolution (monthly to multiyear) variability of observed rainfall. This study has developed a Markov chain (MC) model, which uses a two-state MC process with two parameters (wet-to-wet and dry-to-dry transition probabilities) to simulate rainfall occurrence and a gamma distribution with two parameters (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. Starting with the traditional MC-gamma model with deterministic parameters, this study has developed and assessed four other variants of the MC-gamma model with different parameterisations. The key finding is that if the parameters of the gamma distribution are randomly sampled each year from fitted distributions rather than fixed parameters with time, the variability of rainfall depths at both short and longer temporal resolutions can be preserved, while the variability of wet periods (i.e. number of wet days and mean length of wet spell) can be preserved by decadally varied MC parameters. This is a straightforward enhancement to the traditional simplest MC model and is both objective and parsimonious. © Author(s) 2017. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78954
Appears in Collections: 气候变化事实与影响
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作者单位: School of Engineering, University of Newcastle, Callaghan, NSW, Australia; School of Environmental and Life Sciences, University of Newcastle, Callaghan, NSW, Australia; Department of Civil Engineering, International University of Business Agriculture and Technology, Dhaka, Bangladesh
Recommended Citation:
Chowdhury A,F,M,et al. Development and evaluation of a stochastic daily rainfall model with long-term variability[J]. Hydrology and Earth System Sciences,2017-01-01,21(12)