Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019WR025844 |
Distribution-Based Global Sensitivity Analysis in Hydrology | |
Ciriello, Valentina1; Lauriola, Ilaria1; Tartakovsky, Daniel M.2 | |
2019-11-08 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2019 |
文章类型 | Article;Early Access |
语种 | 英语 |
国家 | Italy; USA |
英文摘要 | Global sensitivity analysis (GSA) is routinely used in academic setting to quantify the influence of input variability and uncertainty on predictions of a quantity of interest. Practical applications of GSA are hampered by its high computational cost, which arises from the need to run large (e.g., groundwater) models multiple times, and by its reliance on the analysis of variance, which formally requires input parameters to be uncorrelated. The former difficulty can be alleviated by replacing expensive models with inexpensive (e.g., polynomial) surrogates, while adoption of distribution-based (rather than variance-based) metrics can, in principle, overcome the latter but at significantly increased computational cost. To make use of distribution-based GSA feasible for regional-scale models with a large number of degrees of freedom, we supplement it with a surrogate model built with polynomial chaos expansions with analytically updated coefficients. We demonstrate the computational efficiency of our algorithm on a case study dealing with evaluation of the effects of temperature variability on annual evapotranspiration at the regional scale. |
英文关键词 | uncertainty surrogate model polynomial chaos evapotranspiration |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000495174400001 |
WOS关键词 | POLYNOMIAL CHAOS ; UNCERTAINTY ; MODEL ; PARAMETERS ; IMPACT ; RISKS |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/223877 |
专题 | 资源环境科学 |
作者单位 | 1.Univ Bologna, DICAM, Bologna, Italy; 2.Stanford Univ, Dept Energy Resources Engn, Stanford, CA 94305 USA |
推荐引用方式 GB/T 7714 | Ciriello, Valentina,Lauriola, Ilaria,Tartakovsky, Daniel M.. Distribution-Based Global Sensitivity Analysis in Hydrology[J]. WATER RESOURCES RESEARCH,2019. |
APA | Ciriello, Valentina,Lauriola, Ilaria,&Tartakovsky, Daniel M..(2019).Distribution-Based Global Sensitivity Analysis in Hydrology.WATER RESOURCES RESEARCH. |
MLA | Ciriello, Valentina,et al."Distribution-Based Global Sensitivity Analysis in Hydrology".WATER RESOURCES RESEARCH (2019). |
条目包含的文件 | 条目无相关文件。 |
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