Dynamic Data Assimilation is a computational framework that systematically integrates sequential observational data with dynamic simulation models to iteratively update and refine the state estimates of a time-evolving geological system.
89
Publications
6.9K
Citations
264
Authors
155
Institutions
Publications per year
2017–2026
30
Parents
Publications
89
Data assimilation methods in the Earth sciences
Rolf H. Reichle · Advances in Water Resources · 2008 · 596 citations
1–5 of 89
Authors
264
- DZ
5
h-index
- LJ
4
h-index
- HC
3
h-index
- LL
3
h-index
- DP
3
h-index
1–5 of 264
Institutions
155
Stanford University
Stanford, United States
7 h-index
14 publications
2K citations
Centre National de la Recherche Scientifique
Paris, France
6 h-index
9 publications
460 citations
University of Illinois Urbana-Champaign
Urbana, United States
5 h-index
5 publications
147 citations
University of Reading
Reading, United Kingdom
4 h-index
7 publications
501 citations
Los Alamos National Laboratory
Los Alamos, United States
4 h-index
20 publications
2K citations
University of Oklahoma
Norman, United States
4 h-index
7 publications
895 citations
Chinese Academy of Sciences
Beijing, China
4 h-index
4 publications
108 citations
Virginia Tech
Blacksburg, United States
3 h-index
4 publications
83 citations
1–8 of 155
Venues
- Advances in Water Resources
7 publications · 1.5K citations
7
h-index
- Journal of Computational Physics
2 publications · 417 citations
3
h-index
- Journal of Hydrology
3 publications · 155 citations
3
h-index
- Journal of Petroleum Science and Engineering
3 publications · 220 citations
3
h-index
- Earth-Science Reviews
1 publications · 35 citations
3
h-index
1–5