Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2016WR019756 |
A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling | |
Dai, Heng1; Chen, Xingyuan1; Ye, Ming2; Song, Xuehang1; Zachara, John M.1 | |
2017-05-01 | |
发表期刊 | WATER RESOURCES RESEARCH
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ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2017 |
卷号 | 53期号:5 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study, we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multilayer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially distributed input variables. |
英文关键词 | sensitivity analysis variance decomposition parametric uncertainty model uncertainty groundwater transport modeling geostatistics |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000403712100047 |
WOS关键词 | DISTRIBUTED HYDROLOGICAL MODEL ; UNSATURATED FRACTURED TUFF ; POLYNOMIAL CHAOS EXPANSION ; HANFORD 300 AREA ; GLOBAL SENSITIVITY ; AQUIFER CHARACTERIZATION ; RADIONUCLIDE MIGRATION ; PARAMETRIC UNCERTAINTY ; CONCEPTUAL-MODEL ; FRAMEWORK |
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/20821 |
专题 | 资源环境科学 |
作者单位 | 1.Pacific Northwest Natl Lab, Richland, WA 99352 USA; 2.Florida State Univ, Dept Comp Sci, Tallahassee, FL 32306 USA |
推荐引用方式 GB/T 7714 | Dai, Heng,Chen, Xingyuan,Ye, Ming,et al. A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling[J]. WATER RESOURCES RESEARCH,2017,53(5). |
APA | Dai, Heng,Chen, Xingyuan,Ye, Ming,Song, Xuehang,&Zachara, John M..(2017).A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling.WATER RESOURCES RESEARCH,53(5). |
MLA | Dai, Heng,et al."A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling".WATER RESOURCES RESEARCH 53.5(2017). |
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