| Year |
Citation |
Score |
| 2020 |
Zhang J, Vrugt JA, Shi X, Lin G, Wu L, Zeng L. Improving Simulation Efficiency of MCMC for Inverse Modeling of Hydrologic Systems With a Kalman‐Inspired Proposal Distribution Water Resources Research. 56. DOI: 10.1029/2019Wr025474 |
0.481 |
|
| 2020 |
Rahmati M, Vanderborght J, Šimůnek J, Vrugt JA, Moret‐Fernández D, Latorre B, Lassabatere L, Vereecken H. Soil hydraulic properties estimation from one‐dimensional infiltration experiments using characteristic time concept Vadose Zone Journal. 19. DOI: 10.1002/Vzj2.20068 |
0.328 |
|
| 2019 |
Yatheendradas S, Kirschbaum D, Nearing G, Vrugt JA, Baum RL, Wooten R, Lu N, Godt JW. Bayesian analysis of the impact of rainfall data product on simulated slope failure for North Carolina locations. Computational Geosciences. 23: 495-522. PMID 33505211 DOI: 10.1007/S10596-018-9804-Y |
0.509 |
|
| 2019 |
Massoud EC, Xu C, Fisher RA, Knox RG, Walker AP, Serbin SP, Christoffersen BO, Holm JA, Kueppers LM, Ricciuto DM, Wei L, Johnson DJ, Chambers JQ, Koven CD, McDowell NG, ... Vrugt JA, et al. Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES) Geoscientific Model Development. 12: 4133-4164. DOI: 10.5194/Gmd-12-4133-2019 |
0.475 |
|
| 2019 |
Moghadas D, Vrugt JA. The Influence of Geostatistical Prior Modeling on the Solution of DCT-Based Bayesian Inversion: A Case Study from Chicken Creek Catchment Remote Sensing. 11: 1549. DOI: 10.3390/Rs11131549 |
0.445 |
|
| 2018 |
Massoud EC, Huisman J, Benincà E, Dietze MC, Bouten W, Vrugt JA. Probing the limits of predictability: data assimilation of chaotic dynamics in complex food webs. Ecology Letters. 21: 93-103. PMID 29178243 DOI: 10.1111/Ele.12876 |
0.403 |
|
| 2018 |
Bakker MM, Heuvelink GB, Vrugt JA, Polman N, Brookhuis B, Kuhlman T. A numerical method to account for distance in a farmer’s willingness to pay for land Spatial Statistics. 25: 22-34. DOI: 10.1016/J.Spasta.2018.04.001 |
0.374 |
|
| 2018 |
de Souza F, Mosslemi M, Vrugt JA, Jin W. Microscopic Simulation Replicates the Capacity Drop Phenomenon Procedia Computer Science. 130: 908-913. DOI: 10.1016/J.Procs.2018.04.088 |
0.432 |
|
| 2018 |
Vrugt JA, Beven KJ. Embracing equifinality with efficiency: Limits of Acceptability sampling using the DREAM(LOA) algorithm Journal of Hydrology. 559: 954-971. DOI: 10.1016/J.Jhydrol.2018.02.026 |
0.374 |
|
| 2018 |
Qin H, Vrugt JA, Xie X, Zhou Y. Improved characterization of underground structure defects from two-stage Bayesian inversion using crosshole GPR data Automation in Construction. 95: 233-244. DOI: 10.1016/J.Autcon.2018.08.014 |
0.302 |
|
| 2017 |
Shockley EM, Vrugt JA, Lopez CF. PyDREAM: High-dimensional parameter inference for biological models in Python. Bioinformatics (Oxford, England). PMID 29028896 DOI: 10.1093/Bioinformatics/Btx626 |
0.536 |
|
| 2017 |
Zhang H, Hendricks Franssen H, Han X, Vrugt JA, Vereecken H. State and parameter estimation of two land surface models using the ensemble Kalman filter and the particle filter Hydrology and Earth System Sciences. 21: 4927-4958. DOI: 10.5194/Hess-21-4927-2017 |
0.486 |
|
| 2017 |
Gomes GJ, Vrugt JA, Vargas EA, Camargo JT, Velloso RQ, van Genuchten MT. The role of uncertainty in bedrock depth and hydraulic properties on the stability of a variably-saturated slope Computers and Geotechnics. 88: 222-241. DOI: 10.1016/J.Compgeo.2017.03.016 |
0.421 |
|
| 2017 |
Brunetti C, Linde N, Vrugt JA. Bayesian model selection in hydrogeophysics: Application to conceptual subsurface models of the South Oyster Bacterial Transport Site, Virginia, USA Advances in Water Resources. 102: 127-141. DOI: 10.1016/J.Advwatres.2017.02.006 |
0.448 |
|
| 2017 |
Volpi E, Schoups G, Firmani G, Vrugt JA. Sworn testimony of the model evidence: Gaussian Mixture Importance (GAME) sampling Water Resources Research. 53: 6133-6158. DOI: 10.1002/2016Wr020167 |
0.478 |
|
| 2017 |
Luke A, Vrugt JA, AghaKouchak A, Matthew R, Sanders BF. Predicting nonstationary flood frequencies: Evidence supports an updated stationarity thesis in the United States Water Resources Research. 53: 5469-5494. DOI: 10.1002/2016Wr019676 |
0.474 |
|
| 2017 |
Post H, Vrugt JA, Fox A, Vereecken H, Hendricks Franssen H. Estimation of Community Land Model parameters for an improved assessment of net carbon fluxes at European sites Journal of Geophysical Research: Biogeosciences. 122: 661-689. DOI: 10.1002/2015Jg003297 |
0.324 |
|
| 2016 |
Ali AA, Xu C, Rogers A, Fisher RA, Wullschleger SD, Massoud EC, Vrugt JA, Muss JD, McDowell NG, Fisher JB, Reich PB, Wilson CJ. A global scale mechanistic model of photosynthetic capacity (LUNA V1.0) Geoscientific Model Development. 9: 587-606. DOI: 10.5194/Gmd-9-587-2016 |
0.394 |
|
| 2016 |
Vereecken H, Schnepf A, Hopmans JW, Javaux M, Or D, Roose T, Vanderborght J, Young MH, Amelung W, Aitkenhead M, Allison SD, Assouline S, Baveye P, Berli M, Brüggemann N, ... ... Vrugt JA, et al. Modeling soil processes: Review, key challenges, and new perspectives Vadose Zone Journal. 15: 1-57. DOI: 10.2136/Vzj2015.09.0131 |
0.389 |
|
| 2016 |
Sadegh M, Vrugt JA, Gupta HV, Xu C. The soil water characteristic as new class of closed-form parametric expressions for the flow duration curve Journal of Hydrology. 535: 438-456. DOI: 10.1016/J.Jhydrol.2016.01.027 |
0.721 |
|
| 2016 |
Vrugt JA. Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation Environmental Modelling and Software. 75: 273-316. DOI: 10.1016/J.Envsoft.2015.08.013 |
0.454 |
|
| 2016 |
Gomes GJC, Vrugt JA, Vargas EA. Toward improved prediction of the bedrock depth underneath hillslopes: Bayesian inference of the bottom-up control hypothesis using high-resolution topographic data Water Resources Research. 52: 3085-3112. DOI: 10.1002/2015Wr018147 |
0.523 |
|
| 2015 |
Askarizadeh A, Rippy MA, Fletcher TD, Feldman DL, Peng J, Bowler P, Mehring AS, Winfrey BK, Vrugt JA, AghaKouchak A, Jiang SC, Sanders BF, Levin LA, Taylor S, Grant SB. From Rain Tanks to Catchments: Use of Low-Impact Development To Address Hydrologic Symptoms of the Urban Stream Syndrome. Environmental Science & Technology. PMID 26317612 DOI: 10.1021/Acs.Est.5B01635 |
0.31 |
|
| 2015 |
Ali AA, Xu C, Rogers A, Fisher RA, Wullschleger SD, McDowell NG, Massoud EC, Vrugt JA, Muss JD, Fisher JB, Reich PB, Wilson CJ. A global scale mechanistic model of the photosynthetic capacity Geoscientific Model Development Discussions. 8: 6217-6266. DOI: 10.5194/Gmdd-8-6217-2015 |
0.378 |
|
| 2015 |
Skaggs TH, Young MH, Vrugt JA. Reproducible research in vadose zone sciences Vadose Zone Journal. 14. DOI: 10.2136/Vzj2015.06.0088 |
0.318 |
|
| 2015 |
Lochbühler T, Vrugt JA, Sadegh M, Linde N. Summary statistics from training images as prior information in probabilistic inversion Geophysical Journal International. 201: 157-171. DOI: 10.1093/Gji/Ggv008 |
0.72 |
|
| 2015 |
Sperna Weiland FC, Vrugt JA, van Beek RLPH, Weerts AH, Bierkens MFP. Significant uncertainty in global scale hydrological modeling from precipitation data errors Journal of Hydrology. 529: 1095-1115. DOI: 10.1016/J.Jhydrol.2015.08.061 |
0.524 |
|
| 2015 |
Qin H, Xie X, Vrugt JA, Zeng K, Hong G. Underground structure defect detection and reconstruction using crosshole GPR and Bayesian waveform inversion Automation in Construction. DOI: 10.1016/J.Autcon.2016.03.011 |
0.375 |
|
| 2015 |
Vrugt J, Laloy E, Linde N, Jacques D. Joint probabilistic inference of multi-Gaussian conductivity fields and their associated variograms from indirect hydrological data Water Resources Research. DOI: 10.1002/2014Wrcr.Xxxx |
0.54 |
|
| 2015 |
Sadegh M, Vrugt JA, Xu C, Volpi E. The stationarity paradigm revisited: Hypothesis testing using diagnostics, summary metrics, and DREAM(ABC) Water Resources Research. 51: 9207-9231. DOI: 10.1002/2014Wr016805 |
0.723 |
|
| 2015 |
Kikuchi CP, Ferré TPA, Vrugt JA. On the optimal design of experiments for conceptual and predictive discrimination of hydrologic system models Water Resources Research. 51: 4454-4481. DOI: 10.1002/2014Wr016795 |
0.433 |
|
| 2015 |
Laloy E, Linde N, Jacques D, Vrugt JA. Probabilistic inference of multi-Gaussian fields from indirect hydrological data using circulant embedding and dimensionality reduction Water Resources Research. 51: 4224-4243. DOI: 10.1002/2014Wr016395 |
0.481 |
|
| 2014 |
Rosas-Carbajal M, Linde N, Kalscheuer T, Vrugt JA. Two-dimensional probabilistic inversion of plane-wave electromagnetic data: Methodology, model constraints and joint inversion with electrical resistivity data Geophysical Journal International. 196: 1508-1524. DOI: 10.1093/Gji/Ggt482 |
0.508 |
|
| 2014 |
De Lannoy GJM, Reichle RH, Vrugt JA. Uncertainty quantification of GEOS-5 L-band radiative transfer model parameters using Bayesian inference and SMOS observations Remote Sensing of Environment. 148: 146-157. DOI: 10.1016/J.Rse.2014.03.030 |
0.463 |
|
| 2014 |
Lochbühler T, Breen SJ, Detwiler RL, Vrugt JA, Linde N. Probabilistic electrical resistivity tomography of a CO2 sequestration analog Journal of Applied Geophysics. 107: 80-92. DOI: 10.1016/J.Jappgeo.2014.05.013 |
0.447 |
|
| 2014 |
Maier HR, Kapelan Z, Kasprzyk J, Kollat J, Matott LS, Cunha MC, Dandy GC, Gibbs MS, Keedwell E, Marchi A, Ostfeld A, Savic D, Solomatine DP, Vrugt JA, Zecchin AC, et al. Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions Environmental Modelling and Software. 62: 271-299. DOI: 10.1016/J.Envsoft.2014.09.013 |
0.352 |
|
| 2014 |
Sadegh M, Vrugt JA. Approximate Bayesian Computation using Markov Chain Monte Carlo simulation: DREAM(ABC) Water Resources Research. 50. DOI: 10.1002/2014Wr015386 |
0.713 |
|
| 2014 |
Vrugt JA, Laloy E. Reply to comment by Chu et al. on "high-dimensional posterior exploration of hydrologic models using multiple-try DREAM (ZS) and high-performance computing", Water Resources Research. 50: 2781-2786. DOI: 10.1002/2013Wr014425 |
0.393 |
|
| 2013 |
Flombaum P, Gallegos JL, Gordillo RA, Rincón J, Zabala LL, Jiao N, Karl DM, Li WK, Lomas MW, Veneziano D, Vera CS, Vrugt JA, Martiny AC. Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus. Proceedings of the National Academy of Sciences of the United States of America. 110: 9824-9. PMID 23703908 DOI: 10.1073/Pnas.1307701110 |
0.368 |
|
| 2013 |
Sadegh M, Vrugt JA. Approximate Bayesian Computation in hydrologic modeling: equifinality of formal and informal approaches Hydrology and Earth System Sciences Discussions. 10: 4739-4797. DOI: 10.5194/HESSD-10-4739-2013 |
0.402 |
|
| 2013 |
Sadegh M, Vrugt JA. Bridging the gap between GLUE and formal statistical approaches: Approximate Bayesian computation Hydrology and Earth System Sciences. 17: 4831-4850. DOI: 10.5194/Hess-17-4831-2013 |
0.723 |
|
| 2013 |
Linde N, Vrugt JA. Distributed soil moisture from crosshole ground-penetrating radar travel times using stochastic inversion Vadose Zone Journal. 12. DOI: 10.2136/Vzj2012.0101 |
0.455 |
|
| 2013 |
Rings J, Kamai T, Kandelous M, Hartsough P, Simunek J, Vrugt J, Hopmans J. Bayesian Inference of Tree Water Relations Using a Soil-Tree-Atmosphere Continuum Model Procedia Environmental Sciences. 19: 26-36. DOI: 10.1016/J.Proenv.2013.06.004 |
0.428 |
|
| 2013 |
Vrugt JA, ter Braak CJF, Diks CGH, Schoups G. Hydrologic data assimilation using particle Markov chain Monte Carlo simulation: Theory, concepts and applications Advances in Water Resources. 51: 457-478. DOI: 10.1016/J.Advwatres.2012.04.002 |
0.484 |
|
| 2013 |
Vrugt JA, Sadegh M. Toward diagnostic model calibration and evaluation: Approximate Bayesian computation Water Resources Research. 49: 4335-4345. DOI: 10.1002/Wrcr.20354 |
0.728 |
|
| 2013 |
Nasta P, Vrugt JA, Romano N. Prediction of the saturated hydraulic conductivity from Brooks and Corey's water retention parameters Water Resources Research. 49: 2918-2925. DOI: 10.1002/Wrcr.20269 |
0.456 |
|
| 2013 |
Nasta P, Romano N, Assouline S, Vrugt JA, Hopmans JW. Prediction of spatially variable unsaturated hydraulic conductivity using scaled particle-size distribution functions Water Resources Research. 49: 4219-4229. DOI: 10.1002/Wrcr.20255 |
0.382 |
|
| 2013 |
Laloy E, Rogiers B, Vrugt JA, Mallants D, Jacques D. Efficient posterior exploration of a high-dimensional groundwater model from two-stage Markov chain Monte Carlo simulation and polynomial chaos expansion Water Resources Research. 49: 2664-2682. DOI: 10.1002/Wrcr.20226 |
0.436 |
|
| 2012 |
Partridge DG, Vrugt JA, Tunved P, Ekman AML, Struthers H, Sorooshian A. Inverse modelling of cloud-aerosol interactions - Part 2: Sensitivity tests on liquid phase clouds using a Markov chain Monte Carlo based simulation approach Atmospheric Chemistry and Physics. 12: 2823-2847. DOI: 10.5194/Acp-12-2823-2012 |
0.432 |
|
| 2012 |
Bikowski J, Huisman JA, Vrugt JA, Vereecken H, Van Kruk JD. Integrated analysis of wave Near Surface Geophysics. 10: 641-652. DOI: 10.3997/1873-0604.2012041 |
0.434 |
|
| 2012 |
Huisman JA, Vrugt JA, Ferre TPA. Vadose zone model-data fusion: State of the art and future challenges Vadose Zone Journal. 11. DOI: 10.2136/Vzj2012.0140 |
0.379 |
|
| 2012 |
Rings J, Vrugt JA, Schoups G, Huisman JA, Vereecken H. Bayesian model averaging using particle filtering and Gaussian mixture modeling: Theory, concepts, and simulation experiments Water Resources Research. 48. DOI: 10.1029/2011Wr011607 |
0.351 |
|
| 2012 |
Laloy E, Linde N, Vrugt JA. Mass conservative three-dimensional water tracer distribution from Markov chain Monte Carlo inversion of time-lapse ground-penetrating radar data Water Resources Research. 48. DOI: 10.1029/2011Wr011238 |
0.474 |
|
| 2012 |
Gupta HV, Clark MP, Vrugt JA, Abramowitz G, Ye M. Towards a comprehensive assessment of model structural adequacy Water Resources Research. 48. DOI: 10.1029/2011Wr011044 |
0.462 |
|
| 2012 |
Laloy E, Vrugt JA. High-dimensional posterior exploration of hydrologic models using multiple-try DREAM (ZS) and high-performance computing Water Resources Research. 48. DOI: 10.1029/2011Wr010608 |
0.535 |
|
| 2012 |
Kandelous MM, Kamai T, Vrugt JA, Šimůnek J, Hanson B, Hopmans JW. Evaluation of subsurface drip irrigation design and management parameters for alfalfa Agricultural Water Management. 109: 81-93. DOI: 10.1016/J.Agwat.2012.02.009 |
0.43 |
|
| 2012 |
Dekker SC, Vrugt JA, Elkington RJ. Significant variation in vegetation characteristics and dynamics from ecohydrological optimality of net carbon profit Ecohydrology. 5: 1-18. DOI: 10.1002/Eco.177 |
0.458 |
|
| 2012 |
Wöhling T, Gayler S, Ingwersen J, Streck T, Vrugt JA, Priesack E. Multiobjective calibration of coupled soil-vegetation-atmosphere models Iahs-Aish Publication. 355: 357-363. |
0.366 |
|
| 2011 |
Vrugt JA. DREAM<sub>(D)</sub>: an adaptive markov chain monte carlo simulation algorithm to solve discrete, noncontinuous, posterior parameter estimation problems Hydrology and Earth System Sciences Discussions. 8: 4025-4052. DOI: 10.5194/HESSD-8-4025-2011 |
0.364 |
|
| 2011 |
Scharnagl B, Vrugt JA, Vereecken H, Herbst M. Bayesian inverse modelling of in situ soil water dynamics: using prior information about the soil hydraulic properties Hydrology and Earth System Sciences Discussions. 8: 2019-2063. DOI: 10.5194/Hessd-8-2019-2011 |
0.444 |
|
| 2011 |
Vrugt JA, Ter Braak CJF. DREAM(D): An adaptive Markov Chain Monte Carlo simulation algorithm to solve discrete, noncontinuous, and combinatorial posterior parameter estimation problems Hydrology and Earth System Sciences. 15: 3701-3713. DOI: 10.5194/Hess-15-3701-2011 |
0.478 |
|
| 2011 |
Scharnagl B, Vrugt JA, Vereecken H, Herbst M. Inverse modelling of in situ soil water dynamics: Investigating the effect of different prior distributions of the soil hydraulic parameters Hydrology and Earth System Sciences. 15: 3043-3059. DOI: 10.5194/Hess-15-3043-2011 |
0.474 |
|
| 2011 |
Partridge DG, Vrugt JA, Tunved P, Ekman AML, Gorea D, Sorooshian A. Towards inverse modeling of cloud-aerosol interactions – Part 1: A detailed response surface analysis Atmospheric Chemistry and Physics Discussions. 11: 4749-4806. DOI: 10.5194/Acpd-11-4749-2011 |
0.466 |
|
| 2011 |
Partridge DG, Vrugt JA, Tunved P, Ekman AML, Gorea D, Sorooshian A. Inverse modeling of cloud-aerosol interactions-Part 1: Detailed response surface analysis Atmospheric Chemistry and Physics. 11: 7269-7287. DOI: 10.5194/Acp-11-7269-2011 |
0.377 |
|
| 2011 |
Dane JH, Vrugt JA, Unsal E. Soil hydraulic functions determined from measurements of air permeability, capillary modeling, and high-dimensional parameter estimation Vadose Zone Journal. 10: 459-465. DOI: 10.2136/Vzj2010.0053 |
0.476 |
|
| 2011 |
Bikowski J, Van Der Kruk J, Huisman JA, Vereecken H, Vrugt JA. Explicit consideration of measurement uncertainty during Bayesian inversion of dispersive GPR data 2011 6th International Workshop On Advanced Ground Penetrating Radar, Iwagpr 2011. DOI: 10.1109/IWAGPR.2011.5963840 |
0.348 |
|
| 2011 |
He M, Hogue TS, Franz KJ, Margulis SA, Vrugt JA. Corruption of parameter behavior and regionalization by model and forcing data errors: A Bayesian example using the SNOW17 model Water Resources Research. 47. DOI: 10.1029/2010Wr009753 |
0.498 |
|
| 2011 |
Wöhling T, Vrugt JA. Multiresponse multilayer vadose zone model calibration using Markov chain Monte Carlo simulation and field water retention data Water Resources Research. 47. DOI: 10.1029/2010Wr009265 |
0.563 |
|
| 2011 |
Minasny B, Vrugt JA, McBratney AB. Confronting uncertainty in model-based geostatistics using Markov Chain Monte Carlo simulation Geoderma. 163: 150-162. DOI: 10.1016/J.Geoderma.2011.03.011 |
0.54 |
|
| 2011 |
He M, Hogue TS, Franz KJ, Margulis SA, Vrugt JA. Characterizing parameter sensitivity and uncertainty for a snow model across hydroclimatic regimes Advances in Water Resources. 34: 114-127. DOI: 10.1016/J.Advwatres.2010.10.002 |
0.505 |
|
| 2011 |
Wöhling T, Barkle GF, Bidwell VJ, Dann R, Wall A, Moorhead B, Clague J, Vrugt JA. Dual-domain mixing cell modelling and uncertainty analysis for unsaturated bromide and chloride transport Modsim 2011 - 19th International Congress On Modelling and Simulation - Sustaining Our Future: Understanding and Living With Uncertainty. 662-668. |
0.368 |
|
| 2010 |
Scharnagl B, Vrugt JA, Vereecken H, Herbst M. Information content of incubation experiments for inverse estimation of pools in the Rothamsted carbon model: A Bayesian perspective Biogeosciences. 7: 763-776. DOI: 10.5194/Bg-7-763-2010 |
0.384 |
|
| 2010 |
Kluitenberg GJ, Kamai T, Vrugt JA, Hopmans JW. Effect of probe deflection on dual-probe heat-pulse thermal conductivity measurements Soil Science Society of America Journal. 74: 1537-1540. DOI: 10.2136/Sssaj2010.0016N |
0.307 |
|
| 2010 |
Gourley JJ, Giangrande SE, Hong Y, Flamig ZL, Schuur T, Vrugt JA. Impacts of polarimetric radar observations on hydrologic simulation Journal of Hydrometeorology. 11: 781-796. DOI: 10.1175/2010Jhm1218.1 |
0.431 |
|
| 2010 |
Yilmaz KK, Vrugt JA, Gupta HV, Sorooshian S. Model calibration in watershed hydrology Advances in Data-Based Approaches For Hydrologic Modeling and Forecasting. 53-105. DOI: 10.1142/9789814307987_0003 |
0.457 |
|
| 2010 |
Bikowski J, Van Der Kruk J, Huisman JA, Vereecken H, Vrugt JA. Inversion and sensitivity analysis of GPR data with waveguide dispersion using Markov Chain Monte Carlo simulation Proceedings of the 13th Internarional Conference On Ground Penetrating Radar, Gpr 2010. DOI: 10.1109/ICGPR.2010.5550147 |
0.339 |
|
| 2010 |
Schoups G, Vrugt JA. A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non-Gaussian errors Water Resources Research. 46. DOI: 10.1029/2009Wr008933 |
0.456 |
|
| 2010 |
Schoups G, Vrugt JA, Fenicia F, Van De Giesen NC. Corruption of accuracy and efficiency of Markov chain Monte Carlo simulation by inaccurate numerical implementation of conceptual hydrologic models Water Resources Research. 46. DOI: 10.1029/2009Wr008648 |
0.461 |
|
| 2010 |
Keating EH, Doherty J, Vrugt JA, Kang Q. Optimization and uncertainty assessment of strongly nonlinear groundwater models with high parameter dimensionality Water Resources Research. 46. DOI: 10.1029/2009Wr008584 |
0.55 |
|
| 2010 |
Hinnell AC, Ferr TPA, Vrugt JA, Huisman JA, Moysey S, Rings J, Kowalsky MB. Improved extraction of hydrologic information from geophysical data through coupled hydrogeophysical inversion Water Resources Research. 46. DOI: 10.1029/2008Wr007060 |
0.431 |
|
| 2010 |
Vereecken H, Huisman JA, Bogena H, Vanderborght J, Vrugt JA, Hopmans JW. On the value of soil moisture measurements in vadose zone hydrology: A review Water Resources Research. 46. DOI: 10.1029/2008Wr006829 |
0.381 |
|
| 2010 |
Huisman JA, Rings J, Vrugt JA, Sorg J, Vereecken H. Hydraulic properties of a model dike from coupled Bayesian and multi-criteria hydrogeophysical inversion Journal of Hydrology. 380: 62-73. DOI: 10.1016/J.Jhydrol.2009.10.023 |
0.534 |
|
| 2010 |
Blasch KW, Ferré TPA, Vrugt JA. Environmental controls on drainage behavior of an ephemeral stream Stochastic Environmental Research and Risk Assessment. 24: 1077-1087. DOI: 10.1007/S00477-010-0398-8 |
0.391 |
|
| 2010 |
Diks CGH, Vrugt JA. Comparison of point forecast accuracy of model averaging methods in hydrologic applications Stochastic Environmental Research and Risk Assessment. 24: 809-820. DOI: 10.1007/s00477-010-0378-z |
0.375 |
|
| 2009 |
Scharnagl B, Vrugt JA, Vereecken H, Herbst M. Information content of incubation experiments for inverse estimation of pools sizes in the Rothamsted carbon model: a Bayesian approach Biogeosciences Discussions. 6: 9331-9357. DOI: 10.5194/bgd-6-9331-2009 |
0.345 |
|
| 2009 |
Stauffer PH, Vrugt JA, Turin HJ, Gable CW, Soll WE. Untangling diff usion from advection in unsaturated porous media: experimental data, modeling, and parameter uncertainty Vadose Zone Journal. 8: 510-522. DOI: 10.2136/Vzj2008.0055 |
0.518 |
|
| 2009 |
Vrugt JA, Ter Braak CJF, Diks CGH, Robinson BA, Hyman JM, Higdon D. Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling International Journal of Nonlinear Sciences and Numerical Simulation. 10: 273-290. DOI: 10.1515/Ijnsns.2009.10.3.273 |
0.38 |
|
| 2009 |
Vrugt JA, Robinson BA, Hyman JM. Self-adaptive multimethod search for global optimization in real-parameter spaces Ieee Transactions On Evolutionary Computation. 13: 243-259. DOI: 10.1109/Tevc.2008.924428 |
0.342 |
|
| 2009 |
Vrugt JA, ter Braak CJF, Gupta HV, Robinson BA. Response to comment by Keith Beven on "Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling?" Stochastic Environmental Research and Risk Assessment. 23: 1061-1062. DOI: 10.1007/S00477-008-0284-9 |
0.381 |
|
| 2009 |
Vrugt JA, ter Braak CJF, Gupta HV, Robinson BA. Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling? Stochastic Environmental Research and Risk Assessment. 23: 1011-1026. DOI: 10.1007/S00477-008-0274-Y |
0.513 |
|
| 2008 |
Vrugt JA, Stauffer PH, Wöhling T, Robinson BA, Vesselinov VV. Inverse modeling of subsurface flow and transport properties: A review with new developments Vadose Zone Journal. 7: 843-844. DOI: 10.2136/Vzj2007.0078 |
0.507 |
|
| 2008 |
Wöhling T, Vrugt JA, Barkle GF. Comparison of three multiobjective optimization algorithms for inverse modeling of vadose zone hydraulic properties Soil Science Society of America Journal. 72: 305-319. DOI: 10.2136/Sssaj2007.0176 |
0.462 |
|
| 2008 |
Feyen L, Kalas M, Vrugt JA. Semi-distributed parameter optimization and uncertainty assessment for large-scale streamflow simulation using global optimization Hydrological Sciences Journal. 53: 293-308. DOI: 10.1623/Hysj.53.2.293 |
0.486 |
|
| 2008 |
Wöhling T, Vrugt JA. Combining multiobjective optimization and Bayesian model averaging to calibrate forecast ensembles of soil hydraulic models Water Resources Research. 44. DOI: 10.1029/2008Wr007154 |
0.483 |
|
| 2008 |
Harp DR, Dai Z, Wolfsberg AV, Vrugt JA, Robinson BA, Vesselinov VV. Aquifer structure identification using stochastic inversion Geophysical Research Letters. 35. DOI: 10.1029/2008Gl033585 |
0.446 |
|
| 2008 |
Clark MP, Slater AG, Rupp DE, Woods RA, Vrugt JA, Gupta HV, Wagener T, Hay LE. Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models Water Resources Research. 44. DOI: 10.1029/2007Wr006735 |
0.472 |
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| 2008 |
Vrugt JA, ter Braak CJF, Clark MP, Hyman JM, Robinson BA. Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation Water Resources Research. 44. DOI: 10.1029/2007Wr006720 |
0.537 |
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| 2008 |
Behrangi A, Khakbaz B, Vrugt JA, Duan Q, Sorooshian S. Comment on "Dynamically dimensioned search algorithm for computationally efficient watershed model calibration" by Bryan A. Tolson and Christine A. Shoemaker Water Resources Research. 44. DOI: 10.1029/2007Wr006429 |
0.362 |
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| 2008 |
Blasone RS, Vrugt JA, Madsen H, Rosbjerg D, Robinson BA, Zyvoloski GA. Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling Advances in Water Resources. 31: 630-648. DOI: 10.1016/J.Advwatres.2007.12.003 |
0.52 |
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| 2008 |
Ter Braak CJF, Vrugt JA. Differential Evolution Markov Chain with snooker updater and fewer chains Statistics and Computing. 18: 435-446. DOI: 10.1007/S11222-008-9104-9 |
0.368 |
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| 2008 |
Vrugt JA, Diks CGH, Clark MP. Ensemble Bayesian model averaging using Markov Chain Monte Carlo sampling Environmental Fluid Mechanics. 8: 579-595. DOI: 10.1007/S10652-008-9106-3 |
0.473 |
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| 2007 |
Vrugt JA, Robinson BA. Improved evolutionary optimization from genetically adaptive multimethod search. Proceedings of the National Academy of Sciences of the United States of America. 104: 708-11. PMID 17215363 DOI: 10.1073/Pnas.0610471104 |
0.317 |
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| 2007 |
Vrugt JA. Comment on "how effective and efficient are multiobjective evolutionary algorithms at hydrologie model calibration?" by Y. Tang et al, Hydrol. Earth Syst. Sci., 10, 289-307, 2006 Hydrology and Earth System Sciences. 11: 1435-1436. DOI: 10.5194/Hess-11-1435-2007 |
0.395 |
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| 2007 |
Vrugt JA, Van Belle J, Bouten W. Pareto front analysis of flight time and energy use in long-distance bird migration Journal of Avian Biology. 38: 432-442. DOI: 10.1111/J.0908-8857.2007.03909.X |
0.332 |
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| 2007 |
Koller J, Chen Y, Reeves GD, Friedel RHW, Cayton TE, Vrugt JA. Identifying the radiation belt source region by data assimilation Journal of Geophysical Research: Space Physics. 112. DOI: 10.1029/2006Ja012196 |
0.348 |
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| 2007 |
Vrugt JA, Robinson BA. Treatment of uncertainty using ensemble methods: Comparison of sequential data assimilation and Bayesian model averaging Water Resources Research. 43. DOI: 10.1029/2005Wr004838 |
0.475 |
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| 2007 |
Feyen L, Vrugt JA, Nualláin BO, van der Knijff J, De Roo A. Parameter optimisation and uncertainty assessment for large-scale streamflow simulation with the LISFLOOD model Journal of Hydrology. 332: 276-289. DOI: 10.1016/J.Jhydrol.2006.07.004 |
0.547 |
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| 2006 |
Vrugt JA, Neuman SP. Introduction to the special section in Vadose Zone Journal: Parameter identification and uncertainty assessment in the unsaturated zone Vadose Zone Journal. 5: 915-916. DOI: 10.2136/Vzj2006.0098 |
0.392 |
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| 2006 |
Vrugt JA, Gupta HV, Nualláin BO, Bouten W. Real-time data assimilation for operational ensemble streamflow forecasting Journal of Hydrometeorology. 7: 548-565. DOI: 10.1175/Jhm504.1 |
0.489 |
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| 2006 |
Vrugt JA, Clark MP, Diks CGH, Duan Q, Robinson BA. Multi-objective calibration of forecast ensembles using Bayesian model averaging Geophysical Research Letters. 33. DOI: 10.1029/2006Gl027126 |
0.474 |
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| 2006 |
Clark MP, Vrugt JA. Unraveling uncertainties in hydrologic model calibration: Addressing the problem of compensatory parameters Geophysical Research Letters. 33. DOI: 10.1029/2005Gl025604 |
0.485 |
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| 2006 |
Vrugt JA, Gupta HV, Dekker SC, Sorooshian S, Wagener T, Bouten W. Application of stochastic parameter optimization to the Sacramento Soil Moisture Accounting model Journal of Hydrology. 325: 288-307. DOI: 10.1016/J.Jhydrol.2005.10.041 |
0.557 |
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| 2006 |
Vrugt JA, Ó Nualláin B, Robinson BA, Bouten W, Dekker SC, Sloot PMA. Application of parallel computing to stochastic parameter estimation in environmental models Computers and Geosciences. 32: 1139-1155. DOI: 10.1016/J.Cageo.2005.10.015 |
0.488 |
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| 2005 |
Schoups G, Hopmans JW, Young CA, Vrugt JA, Wallender WW, Tanji KK, Panday S. Sustainability of irrigated agriculture in the San Joaquin Valley, California. Proceedings of the National Academy of Sciences of the United States of America. 102: 15352-6. PMID 16230610 DOI: 10.1073/Pnas.0507723102 |
0.393 |
|
| 2005 |
Vrugt JA, Robinson BA, Vesselinov VV. Improved inverse modeling for flow and transport in subsurface media: Combined parameter and state estimation Geophysical Research Letters. 32: 1-5. DOI: 10.1029/2005Gl023940 |
0.514 |
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| 2005 |
Vrugt JA, Diks CGH, Gupta HV, Bouten W, Verstraten JM. Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation Water Resources Research. 41: 1-17. DOI: 10.1029/2004Wr003059 |
0.537 |
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| 2005 |
Schoups G, Hopmans JW, Young CA, Vrugt JA, Wallender WW. Multi-criteria optimization of a regional spatially-distributed subsurface water flow model Journal of Hydrology. 311: 20-48. DOI: 10.1016/J.Jhydrol.2005.01.001 |
0.482 |
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| 2004 |
Jansen B, Nierop KG, Vrugt JA, Verstraten JM. (Un)certainty of overall binding constants of Al with dissolved organic matter determined by the Scatchard approach. Water Research. 38: 1270-80. PMID 14975660 DOI: 10.1016/J.Watres.2003.11.017 |
0.45 |
|
| 2004 |
Raat KJ, Vrugt JA, Bouten W, Tietema A. Towards reduced uncertainty in catchment nitrogen modelling: Quantifying the effect of field observation uncertainty on model calibration Hydrology and Earth System Sciences. 8: 751-763. DOI: 10.5194/Hess-8-751-2004 |
0.486 |
|
| 2004 |
Heimovaara TJ, Huisman JA, Vrugt JA, Bouten W. Obtaining the spatial distribution of water content along a TDR probe using the SCEM-UA Bayesian inverse modeling scheme Vadose Zone Journal. 3: 1128-1145. DOI: 10.2113/3.4.1128 |
0.461 |
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| 2004 |
Vrugt JA, Schoups G, Hopmans JW, Young C, Wallender WW, Harter T, Bouten W. Inverse modeling of large-scale spatially distributed vadose zone properties using global optimization Water Resources Research. 40. DOI: 10.1029/2003Wr002706 |
0.513 |
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| 2004 |
Huisman JA, Bouten W, Vrugt JA, Ferré PA. Accuracy of frequency domain analysis scenarios for the determination of complex dielectric permittivity Water Resources Research. 40. DOI: 10.1029/2002Wr001601 |
0.38 |
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| 2004 |
Hopmans JW, Vrugt JA, Schoups G, Wallender WW. Parameter identification of large-scale spatially distributed vadose zone properties Developments in Water Science. 55: 1297-1304. DOI: 10.1016/S0167-5648(04)80144-8 |
0.503 |
|
| 2003 |
Vrugt JA, Bouten W, Gupta HV, Hopmans JW. Toward Improved Identifiability of Soil Hydraulic Parameters Vadose Zone Journal. 2: 98-113. DOI: 10.2136/Vzj2003.0098 |
0.505 |
|
| 2003 |
Vrugt JA, Bouten W, Gupta HV, Hopmans JW. Toward improved identifiability of soil hydraulic parameters: On the selection of a suitable parametric model Vadose Zone Journal. 2: 98-113. DOI: 10.2113/2.1.98 |
0.513 |
|
| 2003 |
Vrugt JA, Dekker SC, Bouten W. Identification of rainfall interception model parameters from measurements of throughfall and forest canopy storage Water Resources Research. 39. DOI: 10.1029/2003Wr002013 |
0.413 |
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| 2003 |
Vrugt JA, Bouten W, Gupta HV, Sorooshian S. Correction to “Toward improved identifiability of hydrologic model parameters: The information content of experimental data” Water Resources Research. 39. DOI: 10.1029/2003Wr001962 |
0.428 |
|
| 2003 |
Vrugt JA, Gupta HV, Bastidas LA, Bouten W, Sorooshian S. Effective and efficient algorithm for multiobjective optimization of hydrologic models Water Resources Research. 39. DOI: 10.1029/2002Wr001746 |
0.396 |
|
| 2003 |
Vrugt JA, Gupta HV, Bouten W, Sorooshian S. A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters Water Resources Research. 39. DOI: 10.1029/2002Wr001642 |
0.452 |
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| 2002 |
Vrugt JA, Bouten W. Validity of first-order approximations to describe parameter uncertainty in soil hydrologic models Soil Science Society of America Journal. 66: 1740-1751. DOI: 10.2136/Sssaj2002.1740 |
0.53 |
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| 2002 |
Vrugt JA, Bouten W, Gupta HV, Sorooshian S. Toward improved identifiability of hydrologic model parameters: The information content of experimental data Water Resources Research. 38: 481-4813. DOI: 10.1029/2001Wr001118 |
0.5 |
|
| 2002 |
Vrugt JA, Bouten W, Dekker SC, Musters PAD. Transpiration dynamics of an Austrian Pine stand and its forest floor: Identifying controlling conditions using artificial neural networks Advances in Water Resources. 25: 293-303. DOI: 10.1016/S0309-1708(01)00061-6 |
0.359 |
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| 2001 |
Vrugt JA, Hopmans JW, Šimunek J. Calibration of a two-dimensional root water uptake model Soil Science Society of America Journal. 65: 1027-1037. DOI: 10.2136/Sssaj2001.6541027X |
0.435 |
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| 2001 |
Vrugt JA, Bouten W, Weerts AH. Information content of data for identifying soil hydraulic parameters from outflow experiments Soil Science Society of America Journal. 65: 19-27. DOI: 10.2136/Sssaj2001.65119X |
0.506 |
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| 2001 |
Vrugt JA, Van Wijk MT, Hopmans JW, Šimunek J. One-, two-, and three-dimensional root water uptake functions for transient modeling Water Resources Research. 37: 2457-2470. DOI: 10.1029/2000Wr000027 |
0.444 |
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