Search Results - "Vrugt, J.A"

Self-Adaptive Multimethod Search for Global Optimization in Real-Parameter Spaces by Vrugt, J.A., Robinson, B.A., Hyman, J.M.

“…Many different algorithms have been developed in the last few decades for solving complex real-world search and optimization problems. The main focus in this…”
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Hydraulic properties of a model dike from coupled Bayesian and multi-criteria hydrogeophysical inversion by Huisman, J.A., Rings, J., Vrugt, J.A., Sorg, J., Vereecken, H.

“…Coupled hydrogeophysical inversion aims to improve the use of geophysical data for hydrological model parameterization. Several numerical studies have…”
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The soil water characteristic as new class of closed-form parametric expressions for the flow duration curve by Sadegh, M., Vrugt, J.A., Gupta, H.V., Xu, C.

“…•The flow duration curve (FDC) is an important signature of catchment behavior.•We review existing FDC models and show that they not always fit well the…”
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Analysing trade-offs in resource and labour allocation by smallholder farmers using inverse modelling techniques: A case-study from Kakamega district, western Kenya by Tittonell, P., van Wijk, M.T., Rufino, M.C., Vrugt, J.A., Giller, K.E.

“…Smallholder farms in sub-Saharan Africa face multiple trade-offs when deciding on the allocation of their financial, labour and nutrient resources. Day-to-day…”
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Multi-criteria optimization of a regional spatially-distributed subsurface water flow model by Schoups, G., Hopmans, J.W., Young, C.A., Vrugt, J.A., Wallender, W.W.

“…This paper presents the multi-criteria calibration of a regional distributed subsurface water flow model for a 1400 km 2 irrigated agricultural area in the…”
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Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions by Maier, H.R., Kapelan, Z., Kasprzyk, J., Kollat, J., Matott, L.S., Cunha, M.C., Dandy, G.C., Gibbs, M.S., Keedwell, E., Marchi, A., Ostfeld, A., Savic, D., Solomatine, D.P., Vrugt, J.A., Zecchin, A.C., Minsker, B.S., Barbour, E.J., Kuczera, G., Pasha, F., Castelletti, A., Giuliani, M., Reed, P.M.

“…The development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active…”
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Hydrologic data assimilation using particle Markov chain Monte Carlo simulation: Theory, concepts and applications by Vrugt, Jasper A., ter Braak, Cajo J.F., Diks, Cees G.H., Schoups, Gerrit

“…During the past decades much progress has been made in the development of computer based methods for parameter and predictive uncertainty estimation of…”
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Treatment of uncertainty using ensemble methods: Comparison of sequential data assimilation and Bayesian model averaging by Vrugt, J.A, Robinson, B.A

“…1 Predictive uncertainty analysis in hydrologic modeling has become an active area of research, the goal being to generate meaningful error bounds on model…”
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Improved extraction of hydrologic information from geophysical data through coupled hydrogeophysical inversion by Hinnell, A.C, Ferre, T.P.A, Vrugt, J.A, Huisman, J.A, Moysey, S, Rings, J, Kowalsky, M.B

“…There is increasing interest in the use of multiple measurement types, including indirect (geophysical) methods, to constrain hydrologic interpretations. To…”
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Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation by Vrugt, Jasper A., ter Braak, Cajo J. F., Clark, Martyn P., Hyman, James M., Robinson, Bruce A.

“…There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit…”
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Differential Evolution Markov Chain with snooker updater and fewer chains by Braak, C.J.F. ter, Vrugt, J.A

“…Differential Evolution Markov Chain (DE-MC) is an adaptive MCMC algorithm, in which multiple chains are run in parallel. Standard DE-MC requires at least N =2…”
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Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling? by Vrugt, Jasper A., ter Braak, Cajo J. F., Gupta, Hoshin V., Robinson, Bruce A.

“…In recent years, a strong debate has emerged in the hydrologic literature regarding what constitutes an appropriate framework for uncertainty estimation…”
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DREAM (D) : an adaptive Markov Chain Monte Carlo simulation algorithm to solve discrete, noncontinuous, and combinatorial posterior parameter estimation problems by Vrugt, J. A., Ter Braak, C. J. F.

“…Formal and informal Bayesian approaches have found widespread implementation and use in environmental modeling to summarize parameter and predictive…”
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Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling by Blasone, R.S, Vrugt, J.A, Madsen, H, Rosbjerg, D, Robinson, B.A, Zyvoloski, G.A

“…In the last few decades hydrologists have made tremendous progress in using dynamic simulation models for the analysis and understanding of hydrologic systems…”
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Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation by Vrugt, J.A, Diks, C.G.H, Gupta, H.V, Bouten, W, Verstraten, J.M

“…Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated…”
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Comparison of Three Multiobjective Optimization Algorithms for Inverse Modeling of Vadose Zone Hydraulic Properties by Wohling, T, Vrugt, J.A, Barkle, G.F

“…Inverse modeling has become increasingly popular for estimating effective hydraulic properties across a range of spatial scales. In recent years, many…”
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Significant uncertainty in global scale hydrological modeling from precipitation data erros by Sperna Weiland, F, Vrugt, J.A, Beek, van, P.H, Weerts, A.H, Bierkens, M.F.P

“…In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient,…”
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Sustainability of irrigated agriculture in the San Joaquin Valley, California by Schoups, G, Hopmans, J.W, Young, C.A, Vrugt, J.A, Wallender, W.W, Tanji, K.K, Panday, S

“…The sustainability of irrigated agriculture in many arid and semiarid areas of the world is at risk because of a combination of several interrelated factors,…”
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Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES) by Massoud, Elias C, Xu, Chonggang, Fisher, Rosie A, Knox, Ryan G, Walker, Anthony P, Serbin, Shawn P, Christoffersen, Bradley O, Holm, Jennifer A, Kueppers, Lara M, Ricciuto, Daniel M, Wei, Liang, Johnson, Daniel J, Chambers, Jeffrey Q, Koven, Charlie D, McDowell, Nate G, Vrugt, Jasper A

“…Vegetation plays an important role in regulating global carbon cycles and is a key component of the Earth system models (ESMs) that aim to project Earth's…”
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Application of stochastic parameter optimization to the Sacramento Soil Moisture Accounting model by Vrugt, Jasper A., Gupta, Hoshin V., Dekker, Stefan C., Sorooshian, Soroosh, Wagener, Thorsten, Bouten, Willem

“…Hydrological models generally contain parameters that cannot be measured directly, but can only be meaningfully inferred by calibration against a historical…”
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