IGSNRR OpenIR
A comparison of simple and complex versions of the Xinanjiang hydrological model in predicting runoff in ungauged basins
Bai, Peng; Liu, Xiaomang; Liang, Kang; Liu, Xiaojie; Liu, Changming
2017-10-01
Source PublicationHYDROLOGY RESEARCH
ISSN1998-9563
Volume48Issue:5Pages:1282-1295
Corresponding AuthorLiu, Xiaomang(liaoxfxm@163.com)
AbstractThere are different views on the selection of hydrological model structural complexity for streamflow prediction in ungauged basins. Some studies suggest that complex models are better than simple models due to the former's prediction capability; whereas some studies favor parsimonious model structures to overcome a risk of over-parameterization. The Xinanjiang (XAJ) model, the most widely used hydrological model in China, has two different versions, as follows: (1) the simple version with seven parameters (XAJ7) and (2) the complex version with 14 parameters (XAJ14). In this study, the two versions of the XAJ model were comprehensively evaluated for streamflow prediction in ungauged basins based on their efficiency, parameter identifiability, and independence. The results showed that the complex XAJ14 model was more flexible than the simple XAJ7 in calibration mode; while the two models have similar performance in validation and regionalization modes. Lack of parameter identifiability and the presence of parameter interdependence most likely explain why the complex XAJ14 cannot consistently outperform the XAJ7 in different modes. Therefore, the simple XAJ7 is a better choice than XAJ14 for streamflow prediction in ungauged basins.
Keywordhydrological modeling model parsimony regionalization ungauged basin Xinanjiang model
DOI10.2166/nh.2016.094
WOS KeywordPARAMETER-ESTIMATION ; FLOW SIMULATION ; LARGE-AREA ; PART 1 ; CATCHMENTS ; PERFORMANCE ; CALIBRATION ; UNCERTAINTY ; STREAMFLOW ; BALANCE
Indexed BySCI
Language英语
Funding ProjectNatural Science Foundation of China[41201034] ; Natural Science Foundation of China[41330529] ; program for 'Bingwei' Excellent Talents in Institute of Geographic Sciences and Natural Resources Research, CAS[2013RC202] ; Chinese Academy of Sciences Visiting Professorship for Senior International Sciences[2013T2Z0014] ; Natural Sciences Foundation of Jiangsu Province[BK20141059]
Funding OrganizationNatural Science Foundation of China ; program for 'Bingwei' Excellent Talents in Institute of Geographic Sciences and Natural Resources Research, CAS ; Chinese Academy of Sciences Visiting Professorship for Senior International Sciences ; Natural Sciences Foundation of Jiangsu Province
WOS Research AreaWater Resources
WOS SubjectWater Resources
WOS IDWOS:000412412500009
PublisherIWA PUBLISHING
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/62362
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLiu, Xiaomang
AffiliationChinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Bai, Peng,Liu, Xiaomang,Liang, Kang,et al. A comparison of simple and complex versions of the Xinanjiang hydrological model in predicting runoff in ungauged basins[J]. HYDROLOGY RESEARCH,2017,48(5):1282-1295.
APA Bai, Peng,Liu, Xiaomang,Liang, Kang,Liu, Xiaojie,&Liu, Changming.(2017).A comparison of simple and complex versions of the Xinanjiang hydrological model in predicting runoff in ungauged basins.HYDROLOGY RESEARCH,48(5),1282-1295.
MLA Bai, Peng,et al."A comparison of simple and complex versions of the Xinanjiang hydrological model in predicting runoff in ungauged basins".HYDROLOGY RESEARCH 48.5(2017):1282-1295.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Bai, Peng]'s Articles
[Liu, Xiaomang]'s Articles
[Liang, Kang]'s Articles
Baidu academic
Similar articles in Baidu academic
[Bai, Peng]'s Articles
[Liu, Xiaomang]'s Articles
[Liang, Kang]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Bai, Peng]'s Articles
[Liu, Xiaomang]'s Articles
[Liang, Kang]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.