DOI: 10.5194/hess-20-887-2016
Scopus记录号: 2-s2.0-84959440436
论文题名: Accounting for dependencies in regionalized signatures for predictions in ungauged catchments
作者: Almeida S ; , Le Vine N ; , McIntyre N ; , Wagener T ; , Buytaert W
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2016
卷: 20, 期: 2 起始页码: 887
结束页码: 901
语种: 英语
Scopus关键词: Errors
; Forecasting
; Probability distributions
; Rain
; Runoff
; Bayesian procedures
; Error correlation structure
; Joint probability distributions
; Observational errors
; Rainfall-runoff modeling
; Rainfall-runoff models
; Regional information
; Response signatures
; Catchments
; catchment
; climate signal
; correlation
; database
; error analysis
; hydrological regime
; prediction
; probability
; rainfall-runoff modeling
; streamflow
英文摘要: A recurrent problem in hydrology is the absence of streamflow data to calibrate rainfall-runoff models. A commonly used approach in such circumstances conditions model parameters on regionalized response signatures. While several different signatures are often available to be included in this process, an outstanding challenge is the selection of signatures that provide useful and complementary information. Different signatures do not necessarily provide independent information and this has led to signatures being omitted or included on a subjective basis. This paper presents a method that accounts for the inter-signature error correlation structure so that regional information is neither neglected nor double-counted when multiple signatures are included. Using 84 catchments from the MOPEX database, observed signatures are regressed against physical and climatic catchment attributes. The derived relationships are then utilized to assess the joint probability distribution of the signature regionalization errors that is subsequently used in a Bayesian procedure to condition a rainfall-runoff model. The results show that the consideration of the inter-signature error structure may improve predictions when the error correlations are strong. However, other uncertainties such as model structure and observational error may outweigh the importance of these correlations. Further, these other uncertainties cause some signatures to appear repeatedly to be misinformative. © Author(s) 2016. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78901
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Civil Engineering, University of Bristol, Bristol, United Kingdom; Department of Civil and Environmental Engineering, Imperial College London, London, United Kingdom; Centre for Water in the Minerals Industry, Sustainable Minerals Institute, University of Queensland, Brisbane, QLD, Australia; Cabot Institute, University of Bristol, Bristol, United Kingdom
Recommended Citation:
Almeida S,, Le Vine N,, McIntyre N,et al. Accounting for dependencies in regionalized signatures for predictions in ungauged catchments[J]. Hydrology and Earth System Sciences,2016-01-01,20(2)