Adaptive Multifidelity Data Assimilation for Nonlinear Subsurface Flow Problems-Reference-Cited by-同舟云学术

Adaptive Multifidelity Data Assimilation for Nonlinear Subsurface Flow Problems

Published:2019-01 Issue:1 Volume:55 Page:203-217
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resour. Res.

Author:

Zheng Qiang¹,Zhang Jiangjiang¹^ORCID,Xu Wenjie²,Wu Laosheng³^ORCID,Zeng Lingzao¹^ORCID

Affiliation:

1. Institute of Soil and Water Resource and Environmental Science, Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, College of Environmental and Resource SciencesZhejiang University Hangzhou China

2. MOE Key Laboratory of Soft Soils and Geoenvironmental Engineering, Institute of Civil EngineeringZhejiang University Hangzhou China

3. Department of Environmental SciencesUniversity of California Riverside CA USA

Funder

National Natural Science Foundation of China

Ministry of Science and Technology of the People's Republic of China

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2018WR023615

Reference63 articles.

1. The Ensemble Kalman Filter in Reservoir Engineering--a Review

2. Approximation errors and model reduction with an application in optical diffusion tomography

3. Modeling Groundwater Flow and Contaminant Transport

4. A surrogate based multi-fidelity approach for robust design optimization

5. Benchmark problems for subsurface flow uncertainty quantification

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