Jasper A. Vrugt
Jasper A. Vrugt
Earth System Science & Engineering
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A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters
JA Vrugt, HV Gupta, W Bouten, S Sorooshian
Water resources research 39 (8), 2003
Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus
P Flombaum, JL Gallegos, RA Gordillo, J Rincón, LL Zabala, N Jiao, ...
Proceedings of the National Academy of Sciences 110 (24), 9824-9829, 2013
Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling
JA Vrugt, CJF ter Braak, CGH Diks, BA Robinson, JM Hyman, D Higdon
International journal of nonlinear sciences and numerical simulation 10 (3 …, 2009
Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation
JA Vrugt, CJF Ter Braak, MP Clark, JM Hyman, BA Robinson
Water Resources Research 44 (12), 2008
On the value of soil moisture measurements in vadose zone hydrology: A review
H Vereecken, JA Huisman, H Bogena, J Vanderborght, JA Vrugt, ...
Water resources research 44 (4), 2008
Effective and efficient algorithm for multiobjective optimization of hydrologic models
JA Vrugt, HV Gupta, LA Bastidas, W Bouten, S Sorooshian
Water resources research 39 (8), 2003
Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation
JA Vrugt
Environmental Modelling & Software 75, 273-316, 2016
Improved evolutionary optimization from genetically adaptive multimethod search
JA Vrugt, BA Robinson
Proceedings of the National Academy of Sciences 104 (3), 708-711, 2007
Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation
JA Vrugt, CGH Diks, HV Gupta, W Bouten, JM Verstraten
Water resources research 41 (1), 2005
Modeling soil processes: Review, key challenges, and new perspectives
H Vereecken, A Schnepf, JW Hopmans, M Javaux, D Or, T Roose, ...
Vadose zone journal 15 (5), vzj2015. 09.0131, 2016
Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions
HR Maier, Z Kapelan, J Kasprzyk, J Kollat, LS Matott, MC Cunha, ...
Environmental Modelling & Software 62, 271-299, 2014
Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models
MP Clark, AG Slater, DE Rupp, RA Woods, JA Vrugt, HV Gupta, ...
Water Resources Research 44 (12), 2008
A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non‐Gaussian errors
G Schoups, JA Vrugt
Water Resources Research 46 (10), 2010
Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling?
JA Vrugt, CJF Ter Braak, HV Gupta, BA Robinson
Stochastic environmental research and risk assessment 23, 1011-1026, 2009
High‐dimensional posterior exploration of hydrologic models using multiple‐try DREAM(ZS) and high‐performance computing
E Laloy, JA Vrugt
Water Resources Research 48 (1), 2012
Differential evolution Markov chain with snooker updater and fewer chains
CJF Ter Braak, JA Vrugt
Statistics and Computing 18, 435-446, 2008
Strong latitudinal patterns in the elemental ratios of marine plankton and organic matter
AC Martiny, CTA Pham, FW Primeau, JA Vrugt, JK Moore, SA Levin, ...
Nature Geoscience 6 (4), 279-283, 2013
Towards a comprehensive assessment of model structural adequacy
HV Gupta, MP Clark, JA Vrugt, G Abramowitz, M Ye
Water Resources Research 48 (8), 2012
Calibration of a two‐dimensional root water uptake model
JA Vrugt, JW Hopmans, J Šimunek
Soil Science Society of America Journal 65 (4), 1027-1037, 2001
Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling
RS Blasone, JA Vrugt, H Madsen, D Rosbjerg, BA Robinson, ...
Advances in Water Resources 31 (4), 630-648, 2008
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