Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019WR024739 |
Bayesian Calibration and Sensitivity Analysis for a Karst Aquifer Model Using Active Subspaces | |
Parente, Mario Teixeira1; Bittner, Daniel2; Mattis, Steven A.1; Chiogna, Gabriele2,3; Wohlmuth, Barbara1 | |
2019-08-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2019 |
卷号 | 55期号:8页码:7086-7107 |
文章类型 | Article |
语种 | 英语 |
国家 | Germany; Austria |
英文摘要 | In this article, we perform a parameter study for a recently developed karst hydrological model. The study consists of a high-dimensional Bayesian inverse problem and a global sensitivity analysis. For the first time in karst hydrology, we use the active subspace method to find directions in the parameter space that dominate the Bayesian update from the prior to the posterior distribution in order to effectively reduce the dimension of the problem and for computational efficiency. Additionally, the calculated active subspace can be exploited to construct sensitivity metrics on each of the individual parameters and be used to construct a natural model surrogate. The model consists of 21 parameters to reproduce the hydrological behavior of spring discharge in a karst aquifer located in the Kerschbaum spring recharge area at Waidhofen a.d. Ybbs in Austria. The experimental spatial and time series data for the inference process were collected by the water works in Waidhofen. We show that this case study has implicit low dimensionality, and we run an adjusted Markov chain Monte Carlo algorithm in a low-dimensional subspace to construct samples of the posterior distribution. The results are visualized and verified by plots of the posterior's push-forward distribution displaying the uncertainty in predicting discharge values due to the experimental noise in the data. Finally, a discussion provides hydrological interpretation of these results for the Kerschbaum area. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000490973700042 |
WOS关键词 | CHAIN MONTE-CARLO ; RECHARGE MODEL ; FLOW ; UNCERTAINTY ; REDUCTION ; SIMULATION ; PARAMETERS ; CONDUITS ; SPRINGS ; IMPACT |
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/185882 |
专题 | 资源环境科学 |
作者单位 | 1.Tech Univ Munich, Chair Numer Math, Munich, Germany; 2.Tech Univ Munich, Chair Hydrol & River Basin Management, Munich, Germany; 3.Univ Innsbruck, Inst Geog, Innsbruck, Austria |
推荐引用方式 GB/T 7714 | Parente, Mario Teixeira,Bittner, Daniel,Mattis, Steven A.,et al. Bayesian Calibration and Sensitivity Analysis for a Karst Aquifer Model Using Active Subspaces[J]. WATER RESOURCES RESEARCH,2019,55(8):7086-7107. |
APA | Parente, Mario Teixeira,Bittner, Daniel,Mattis, Steven A.,Chiogna, Gabriele,&Wohlmuth, Barbara.(2019).Bayesian Calibration and Sensitivity Analysis for a Karst Aquifer Model Using Active Subspaces.WATER RESOURCES RESEARCH,55(8),7086-7107. |
MLA | Parente, Mario Teixeira,et al."Bayesian Calibration and Sensitivity Analysis for a Karst Aquifer Model Using Active Subspaces".WATER RESOURCES RESEARCH 55.8(2019):7086-7107. |
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