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Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications

Xiaomeng Song, Jianyun Zhang, Chesheng Zhan, Yunqing Xuan Orcid Logo, Ming Ye, Chonggang Xu

Journal of Hydrology, Volume: 523, Pages: 739 - 757

Swansea University Author: Yunqing Xuan Orcid Logo

Abstract

Sensitivity analysis (SA) aims to identify the key parameters that affect model performance and it plays important roles in model parameterization, calibration, optimization, and uncertainty quantification. However, the increasing complexity of hydrological models means that a large number of parame...

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Published in: Journal of Hydrology
ISSN: 0022-1694
Published: 2015
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URI: https://cronfa.swan.ac.uk/Record/cronfa21107
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first_indexed 2015-05-07T02:10:09Z
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spelling 2019-08-28T13:33:23.6915147 v2 21107 2015-05-06 Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications 3ece84458da360ff84fa95aa1c0c912b 0000-0003-2736-8625 Yunqing Xuan Yunqing Xuan true false 2015-05-06 CIVL Sensitivity analysis (SA) aims to identify the key parameters that affect model performance and it plays important roles in model parameterization, calibration, optimization, and uncertainty quantification. However, the increasing complexity of hydrological models means that a large number of parameters need to be estimated. To better understand how these complex models work, efficient SA methods should be applied before the application of hydrological modeling. This study provides a comprehensive review of global SA methods in the field of hydrological modeling. The common definitions of SA and the typical categories of SA methods are described. A wide variety of global SA methods have been introduced to provide a more efficient evaluation framework for hydrological modeling. We review, analyze, and categorize research into global SA methods and their applications, with an emphasis on the research accomplished in the hydrological modeling field. The advantages and disadvantages are also discussed and summarized. An application framework and the typical practical steps involved in SA for hydrological modeling are outlined. Further discussions cover several important and often overlooked topics, including the relationship between parameter identification, uncertainty analysis, and optimization in hydrological modeling, how to deal with correlated parameters, and time-varying SA. Finally, some conclusions and guidance recommendations on SA in hydrological modeling are provided, as well as a list of important future research directions that may facilitate more robust analyses when assessing hydrological modeling performance. Journal Article Journal of Hydrology 523 739 757 0022-1694 30 4 2015 2015-04-30 10.1016/j.jhydrol.2015.02.013 COLLEGE NANME Civil Engineering COLLEGE CODE CIVL Swansea University 2019-08-28T13:33:23.6915147 2015-05-06T13:42:36.1934512 College of Engineering Engineering Xiaomeng Song 1 Jianyun Zhang 2 Chesheng Zhan 3 Yunqing Xuan 0000-0003-2736-8625 4 Ming Ye 5 Chonggang Xu 6 0021107-10052016114550.pdf JoH_final_revision_Sensitivity_analysis_[6097548].pdf 2016-05-10T11:45:50.6870000 Output 572540 application/pdf Accepted Manuscript true 2016-05-10T00:00:00.0000000 true
title Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications
spellingShingle Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications
Yunqing Xuan
title_short Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications
title_full Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications
title_fullStr Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications
title_full_unstemmed Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications
title_sort Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications
author_id_str_mv 3ece84458da360ff84fa95aa1c0c912b
author_id_fullname_str_mv 3ece84458da360ff84fa95aa1c0c912b_***_Yunqing Xuan
author Yunqing Xuan
author2 Xiaomeng Song
Jianyun Zhang
Chesheng Zhan
Yunqing Xuan
Ming Ye
Chonggang Xu
format Journal article
container_title Journal of Hydrology
container_volume 523
container_start_page 739
publishDate 2015
institution Swansea University
issn 0022-1694
doi_str_mv 10.1016/j.jhydrol.2015.02.013
college_str College of Engineering
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hierarchy_top_id collegeofengineering
hierarchy_top_title College of Engineering
hierarchy_parent_id collegeofengineering
hierarchy_parent_title College of Engineering
department_str Engineering{{{_:::_}}}College of Engineering{{{_:::_}}}Engineering
document_store_str 1
active_str 0
description Sensitivity analysis (SA) aims to identify the key parameters that affect model performance and it plays important roles in model parameterization, calibration, optimization, and uncertainty quantification. However, the increasing complexity of hydrological models means that a large number of parameters need to be estimated. To better understand how these complex models work, efficient SA methods should be applied before the application of hydrological modeling. This study provides a comprehensive review of global SA methods in the field of hydrological modeling. The common definitions of SA and the typical categories of SA methods are described. A wide variety of global SA methods have been introduced to provide a more efficient evaluation framework for hydrological modeling. We review, analyze, and categorize research into global SA methods and their applications, with an emphasis on the research accomplished in the hydrological modeling field. The advantages and disadvantages are also discussed and summarized. An application framework and the typical practical steps involved in SA for hydrological modeling are outlined. Further discussions cover several important and often overlooked topics, including the relationship between parameter identification, uncertainty analysis, and optimization in hydrological modeling, how to deal with correlated parameters, and time-varying SA. Finally, some conclusions and guidance recommendations on SA in hydrological modeling are provided, as well as a list of important future research directions that may facilitate more robust analyses when assessing hydrological modeling performance.
published_date 2015-04-30T03:39:37Z
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