G. De Lannoy
Global and Planetary Change · 2006–2011
A researcher in the Science corpus: 5 papers; trusts 17 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Global and Planetary Change — 22 citations into it
- Environmental Engineering — 16 citations into it; #1,791 of 5,479 by trust here, #2,691 by citations
- Atmospheric Science — 15 citations into it; #1,505 of 4,804 by trust here, #2,779 by citations
- Water Science and Technology — 15 citations into it; #869 of 1,711 by trust here, #1,275 by citations
- Oceanography — 6 citations into it
Whom G. De Lannoy trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geir Evensen
- Rolf H. Reichle
- Paul R. Houser
- Hoshin V. Gupta
- Soroosh Sorooshian
- C. Keppenne
- Dennis McLaughlin
- Hamid Moradkhani
- Valentijn R. N. Pauwels
- Qingyun Duan
Who trusts G. De Lannoy overall
- Valentijn R. N. Pauwels
- William A. Lahoz
- Philipp Schneider
- D. Plaza
- Dingbao Wang
- Paul R. Houser
- Rolf H. Reichle
- Robain de Keyser
- Niko E. C. Verhoest
- Yuguo Chen
Papers from G. De Lannoy's perspective
Ordered by how strongly the researchers G. De Lannoy trusts endorse each paper. Same corpus, a different order for every researcher.
- Hydrologic Data Assimilation with the Ensemble Kalman Filter
- The Ensemble Kalman Filter: theoretical formulation and practical implementation
- Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter
- Bayesian recursive parameter estimation for hydrologic models
- Novel approach to nonlinear/non-Gaussian Bayesian state estimation
- Shuffled complex evolution approach for effective and efficient global minimization
- Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter
- Dual state-parameter estimation of hydrological models using ensemble Kalman filter
- Towards the characterization of streamflow simulation uncertainty through multimodel ensembles
- Multi-objective global optimization for hydrologic models
Their papers
- The importance of parameter resampling for soil moisture data assimilation into hydrologic models using the particle filter (2011) — 87 citations
- Ensemble‐based assimilation of discharge into rainfall‐runoff models: A comparison of approaches to mapping observational information to state space (2009) — 96 citations
- State and bias estimation for soil moisture profiles by an ensemble Kalman filter: Effect of assimilation depth and frequency (2007) — 114 citations
- Correcting for forecast bias in soil moisture assimilation with the ensemble Kalman filter (2007) — 205 citations
- Assessment of model uncertainty for soil moisture through ensemble verification (2006) — 118 citations