42 citations as recorded by crossref.

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2. Approximate Bayesian Computation using Markov Chain Monte Carlo simulation: DREAM(ABC) M. Sadegh & J. Vrugt 10.1002/2014WR015386
3. Signature‐Domain Calibration of Hydrological Models Using Approximate Bayesian Computation: Theory and Comparison to Existing Applications D. Kavetski et al. 10.1002/2017WR020528
4. Stochastic inversion for soil hydraulic parameters in the presence of model error: An example involving ground-penetrating radar monitoring of infiltration C. Köpke et al. 10.1016/j.jhydrol.2018.12.016
5. Climate‐Induced Changes in the Risk of Hydrological Failure of Major Dams in California I. Mallakpour et al. 10.1029/2018GL081888
6. Using maximum likelihood to derive various distance-based goodness-of-fit indicators for hydrologic modeling assessment Q. Cheng et al. 10.1007/s00477-017-1507-8
7. Comparison of GLUE and DREAM for the estimation of cultivar parameters in the APSIM-maize model M. Sheng et al. 10.1016/j.agrformet.2019.107659
8. Relative model score: a scoring rule for evaluating ensemble simulations with application to microbial soil respiration modeling A. Elshall et al. 10.1007/s00477-018-1592-3
9. Revising tortuosity and multi-fractal assumptions of unsaturated hydraulic conductivity from critical path analysis of percolation theory A. Rad et al. 10.1016/j.geoderma.2019.06.002
10. Robust and efficient uncertainty quantification for extreme events that deviate significantly from the training dataset using polynomial chaos-kriging V. Tran & J. Kim 10.1016/j.jhydrol.2022.127716
11. Multihazard Scenarios for Analysis of Compound Extreme Events M. Sadegh et al. 10.1029/2018GL077317
12. A game theoretical low impact development optimization model for urban storm water management M. Latifi et al. 10.1016/j.jclepro.2019.118323
13. The stationarity paradigm revisited: Hypothesis testing using diagnostics, summary metrics, and DREAM (ABC) M. Sadegh et al. 10.1002/2014WR016805
14. Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale G. Papacharalampous et al. 10.1016/j.advwatres.2019.103470
15. Multi-objective conflict resolution optimization model for reservoir’s selective depth water withdrawal considering water quality M. Haghighat et al. 10.1007/s11356-020-10475-y
16. Copula‐Based Convection‐Permitting Projections of Future Changes in Multivariate Drought Characteristics B. Zhang et al. 10.1029/2019JD030686
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18. Signature‐Domain Calibration of Hydrological Models Using Approximate Bayesian Computation: Empirical Analysis of Fundamental Properties F. Fenicia et al. 10.1002/2017WR021616
19. Probabilistic programming: A review for environmental modellers C. Krapu & M. Borsuk 10.1016/j.envsoft.2019.01.014
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22. Multivariate C opula A nalysis T oolbox (MvCAT): Describing dependence and underlying uncertainty using a B ayesian framework M. Sadegh et al. 10.1002/2016WR020242
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26. A fuzzy multi-objective optimization approach for treated wastewater allocation S. Tayebikhorami et al. 10.1007/s10661-019-7557-2
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28. Bayesian inference and predictive performance of soil respiration models in the presence of model discrepancy A. Elshall et al. 10.5194/gmd-12-2009-2019
29. Improving probabilistic hydroclimatic projections through high-resolution convection-permitting climate modeling and Markov chain Monte Carlo simulations S. Wang & Y. Wang 10.1007/s00382-019-04702-7
30. Approximate B ayesian computation methods for daily spatiotemporal precipitation occurrence simulation B. Olson & W. Kleiber 10.1002/2016WR019741
31. Embracing equifinality with efficiency: Limits of Acceptability sampling using the DREAM(LOA) algorithm J. Vrugt & K. Beven 10.1016/j.jhydrol.2018.02.026
32. Improving Robustness of Hydrologic Ensemble Predictions Through Probabilistic Pre‐ and Post‐Processing in Sequential Data Assimilation S. Wang et al. 10.1002/2018WR022546
33. Parameter estimation for complex thermal-fluid flows using approximate Bayesian computation J. Christopher et al. 10.1103/PhysRevFluids.3.104602
34. Automatic calibration and uncertainty quantification in waves dynamical downscaling R. Alonso & S. Solari 10.1016/j.coastaleng.2021.103944
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36. Considering rating curve uncertainty in water level predictions A. Sikorska et al. 10.5194/hess-17-4415-2013
37. Stochastic inversion for soil hydraulic parameters in the presence of model error: An example involving ground-penetrating radar monitoring of infiltration C. Köpke et al. 10.1016/j.jhydrol.2018.12.016
38. Toward diagnostic model calibration and evaluation: Approximate Bayesian computation J. Vrugt & M. Sadegh 10.1002/wrcr.20354
39. An Improved Bayesian Structural Identification Using the First Two Derivatives of Log-Likelihood Measure J. Zhou et al. 10.1155/2015/236475
40. Estimating hydrologic model uncertainty in the presence of complex residual error structures S. Samadi et al. 10.1007/s00477-017-1489-6
41. Experimental Coupling of TOPMODEL with the National Water Model: Effects of Coupling Interface Complexity on Model Performance D. Kim et al. 10.1111/1752-1688.12953
42. Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation J. Vrugt 10.1016/j.envsoft.2015.08.013