An improved calibration and uncertainty analysis approach using a multicriteria sequential algorithm for hydrological modeling

Abstract Hydrological models are widely used as simplified, conceptual, mathematical representatives for water resource management. The performance of hydrological modeling is usually challenged by model calibration and uncertainty analysis during modeling exercises. In this study, a multicriteria s...

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Autores principales:	Hongjing Wu, Bing Chen, Xudong Ye, Huaicheng Guo, Xianyong Meng, Baiyu Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a846d5077f364bde9e2a231551f7b29a
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spelling	oai:doaj.org-article:a846d5077f364bde9e2a231551f7b29a2021-12-02T15:10:54ZAn improved calibration and uncertainty analysis approach using a multicriteria sequential algorithm for hydrological modeling10.1038/s41598-021-96250-62045-2322https://doaj.org/article/a846d5077f364bde9e2a231551f7b29a2021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-96250-6https://doaj.org/toc/2045-2322Abstract Hydrological models are widely used as simplified, conceptual, mathematical representatives for water resource management. The performance of hydrological modeling is usually challenged by model calibration and uncertainty analysis during modeling exercises. In this study, a multicriteria sequential calibration and uncertainty analysis (MS-CUA) method was proposed to improve the efficiency and performance of hydrological modeling with high reliability. To evaluate the performance and feasibility of the proposed method, two case studies were conducted in comparison with two other methods, sequential uncertainty fitting algorithm (SUFI-2) and generalized likelihood uncertainty estimation (GLUE). The results indicated that the MS-CUA method could quickly locate the highest posterior density regions to improve computational efficiency. The developed method also provided better-calibrated results (e.g., the higher NSE value of 0.91, 0.97, and 0.74) and more balanced uncertainty analysis results (e.g., the largest P/R ratio values of 1.23, 2.15, and 1.00) comparing with other traditional methods for both case studies.Hongjing WuBing ChenXudong YeHuaicheng GuoXianyong MengBaiyu ZhangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Hongjing Wu Bing Chen Xudong Ye Huaicheng Guo Xianyong Meng Baiyu Zhang An improved calibration and uncertainty analysis approach using a multicriteria sequential algorithm for hydrological modeling
description	Abstract Hydrological models are widely used as simplified, conceptual, mathematical representatives for water resource management. The performance of hydrological modeling is usually challenged by model calibration and uncertainty analysis during modeling exercises. In this study, a multicriteria sequential calibration and uncertainty analysis (MS-CUA) method was proposed to improve the efficiency and performance of hydrological modeling with high reliability. To evaluate the performance and feasibility of the proposed method, two case studies were conducted in comparison with two other methods, sequential uncertainty fitting algorithm (SUFI-2) and generalized likelihood uncertainty estimation (GLUE). The results indicated that the MS-CUA method could quickly locate the highest posterior density regions to improve computational efficiency. The developed method also provided better-calibrated results (e.g., the higher NSE value of 0.91, 0.97, and 0.74) and more balanced uncertainty analysis results (e.g., the largest P/R ratio values of 1.23, 2.15, and 1.00) comparing with other traditional methods for both case studies.
format	article
author	Hongjing Wu Bing Chen Xudong Ye Huaicheng Guo Xianyong Meng Baiyu Zhang
author_facet	Hongjing Wu Bing Chen Xudong Ye Huaicheng Guo Xianyong Meng Baiyu Zhang
author_sort	Hongjing Wu
title	An improved calibration and uncertainty analysis approach using a multicriteria sequential algorithm for hydrological modeling
title_short	An improved calibration and uncertainty analysis approach using a multicriteria sequential algorithm for hydrological modeling
title_full	An improved calibration and uncertainty analysis approach using a multicriteria sequential algorithm for hydrological modeling
title_fullStr	An improved calibration and uncertainty analysis approach using a multicriteria sequential algorithm for hydrological modeling
title_full_unstemmed	An improved calibration and uncertainty analysis approach using a multicriteria sequential algorithm for hydrological modeling
title_sort	improved calibration and uncertainty analysis approach using a multicriteria sequential algorithm for hydrological modeling
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/a846d5077f364bde9e2a231551f7b29a
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An improved calibration and uncertainty analysis approach using a multicriteria sequential algorithm for hydrological modeling

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