Comparison of Three Statistical Downscaling Methods and Ensemble Downscaling Method Based on Bayesian Model Averaging in Upper Hanjiang River Basin, China
Joint Authors
Zhang, Liping
Liu, Jiaming
Yuan, Di
Zou, Xia
Song, Xingyuan
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-29
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Many downscaling techniques have been developed in the past few years for projection of station-scale hydrological variables from large-scale atmospheric variables to assess the hydrological impacts of climate change.
To improve the simulation accuracy of downscaling methods, the Bayesian Model Averaging (BMA) method combined with three statistical downscaling methods, which are support vector machine (SVM), BCC/RCG-Weather Generators (BCC/RCG-WG), and Statistics Downscaling Model (SDSM), is proposed in this study, based on the statistical relationship between the larger scale climate predictors and observed precipitation in upper Hanjiang River Basin (HRB).
The statistical analysis of three performance criteria (the Nash-Sutcliffe coefficient of efficiency, the coefficient of correlation, and the relative error) shows that the performance of ensemble downscaling method based on BMA for rainfall is better than that of each single statistical downscaling method.
Moreover, the performance for the runoff modelled by the SWAT rainfall-runoff model using the downscaled daily rainfall by four methods is also compared, and the ensemble downscaling method has better simulation accuracy.
The ensemble downscaling technology based on BMA can provide scientific basis for the study of runoff response to climate change.
American Psychological Association (APA)
Liu, Jiaming& Yuan, Di& Zhang, Liping& Zou, Xia& Song, Xingyuan. 2015. Comparison of Three Statistical Downscaling Methods and Ensemble Downscaling Method Based on Bayesian Model Averaging in Upper Hanjiang River Basin, China. Advances in Meteorology،Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1095631
Modern Language Association (MLA)
Liu, Jiaming…[et al.]. Comparison of Three Statistical Downscaling Methods and Ensemble Downscaling Method Based on Bayesian Model Averaging in Upper Hanjiang River Basin, China. Advances in Meteorology No. 2016 (2016), pp.1-12.
https://search.emarefa.net/detail/BIM-1095631
American Medical Association (AMA)
Liu, Jiaming& Yuan, Di& Zhang, Liping& Zou, Xia& Song, Xingyuan. Comparison of Three Statistical Downscaling Methods and Ensemble Downscaling Method Based on Bayesian Model Averaging in Upper Hanjiang River Basin, China. Advances in Meteorology. 2015. Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1095631
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1095631