Albrecht H. Weerts
Global and Planetary Change · 2001–2014
A researcher in the Science corpus: 4 papers; trusts 15 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Global and Planetary Change — 36 citations into it
- Water Science and Technology — 29 citations into it; #447 of 1,711 by trust here, #908 by citations
- Atmospheric Science — 27 citations into it
- Environmental Engineering — 22 citations into it; #2,019 of 5,479 by trust here, #4,165 by citations
Whom Albrecht H. Weerts trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Hamid Moradkhani
- Neil J. Gordon
- Jun S. Liu
- Hoshin V. Gupta
- Arnaud Doucet
- Soroosh Sorooshian
- M. Sanjeev Arulampalam
- Rong Chen
- Vijay P. Singh
- Dmitri Kavetski
Who trusts Albrecht H. Weerts overall
Papers from Albrecht H. Weerts's perspective
Ordered by how strongly the researchers Albrecht H. Weerts trusts endorse each paper. Same corpus, a different order for every researcher.
- Sequential Monte Carlo methods for dynamic systems
- Effective and efficient global optimization for conceptual rainfall‐runoff models
- The future of distributed models: model calibration and uncertainty prediction.
- Novel approach to nonlinear/non-Gaussian Bayesian state estimation
- A manifesto for the equifinality thesis
- Dual state-parameter estimation of hydrological models using ensemble Kalman filter
- An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction
- Towards the characterization of streamflow simulation uncertainty through multimodel ensembles
- Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters
- Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter
Their papers
- Alternative configurations of quantile regression for estimating predictive uncertainty in water level forecasts for the upper Severn River: A comparison (2014) — 58 citations
- Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities (2012) — 453 citations
- Particle filtering and ensemble Kalman filtering for state updating with hydrological conceptual rainfall‐runoff models (2006) — 364 citations
- Information content of data for identifying soil hydraulic parameters from outflow experiments (2001) — 122 citations