Valentijn R. N. Pauwels
Environmental Engineering · 2006–2017
A researcher in the Science corpus: 8 papers; trusts 22 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Environmental Engineering — 34 citations into it; #1,790 of 5,479 by trust here, #2,609 by citations
- Water Science and Technology — 33 citations into it; #460 of 1,711 by trust here, #1,187 by citations
- Global and Planetary Change — 32 citations into it; #5,400 of 10,225 by trust here, #7,711 by citations
- Atmospheric Science — 16 citations into it; #1,504 of 4,804 by trust here, #2,779 by citations
- Oceanography — 6 citations into it
Whom Valentijn R. N. Pauwels trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Hoshin V. Gupta
- G. De Lannoy
- Soroosh Sorooshian
- Rolf H. Reichle
- Qingyun Duan
- Hamid Moradkhani
- Paul R. Houser
- Jasper A. Vrugt
- Geir Evensen
- Dennis McLaughlin
Who trusts Valentijn R. N. Pauwels overall
Papers from Valentijn R. N. Pauwels's perspective
Ordered by how strongly the researchers Valentijn R. N. Pauwels trusts endorse each paper. Same corpus, a different order for every researcher.
- Hydrologic Data Assimilation with the Ensemble Kalman Filter
- Bayesian recursive parameter estimation for hydrologic models
- Shuffled complex evolution approach for effective and efficient global minimization
- Novel approach to nonlinear/non-Gaussian Bayesian state estimation
- Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter
- The future of distributed models: model calibration and uncertainty prediction.
- Dual state-parameter estimation of hydrological models using ensemble Kalman filter
- Optimal use of the SCE-UA global optimization method for calibrating watershed models
- Towards the characterization of streamflow simulation uncertainty through multimodel ensembles
- Sequential Monte Carlo methods for dynamic systems
Their papers
- The evolution of process-based hydrologic models: Historical challenges and the collective quest for physical realism. (2017) — 311 citations
- The importance of parameter resampling for soil moisture data assimilation into hydrologic models using the particle filter (2011) — 87 citations
- Calibration of a water and energy balance model: Recursive parameter estimation versus particle swarm optimization (2009) — 47 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
- Improvement of the PEST parameter estimation algorithm through Extended Kalman Filtering (2007) — 50 citations
- Assessment of model uncertainty for soil moisture through ensemble verification (2006) — 118 citations