Rating curve estimation under epistemic uncertainty

被引:75
|
作者
McMillan, H. K. [1 ]
Westerberg, I. K. [2 ,3 ]
机构
[1] Natl Inst Water & Atmospher Res, Christchurch, New Zealand
[2] Univ Bristol, Dept Civil Engn, Bristol, Avon, England
[3] IVL Swedish Environm Res Inst, Stockholm, Sweden
关键词
epistemic; uncertainty; rating curve; likelihood; discharge; aleatory; BAYESIAN METHODS; MODELS; RIVER; COMPUTATION; CALIBRATION; REGRESSION; STATIONS; ERROR;
D O I
10.1002/hyp.10419
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
River discharge values, estimated using a rating curve, are subject to both random and epistemic errors. We present a new likelihood function, the Voting Point' likelihood that accounts for both error types and enables generation of multiple possible multisegment power-law rating curve samples that aim to represent the total uncertainty. The rating curve samples can be used for subsequent discharge analysis that needs total uncertainty estimation, e.g. regionalisation studies or calculation of hydrological signatures. We demonstrate the method using four catchments with diverse rating curve error characteristics, where epistemic uncertainty sources include weed growth, scour and redeposition of the bed gravels in a braided river, and unconfined high flows. The results show that typically, the posterior rating curve distributions include all of the gauging points and succeed in representing the spread of discharge values caused by epistemic rating errors. We aim to provide a useful method for hydrology practitioners to assess rating curve, and hence discharge, uncertainty that is easily applicable to a wide range of catchments and does not require prior specification of the particular types and causes of epistemic error at the gauged location. Copyright (c) 2014 John Wiley & Sons, Ltd.
引用
收藏
页码:1873 / 1882
页数:10
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