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Efficient posterior exploration of a high‐dimensional groundwater model from two‐stage Markov chain Monte Carlo simulation and polynomial chaos expansion
Advancing parameter uncertainty quantification in hydrology models through integration of variational inference with a differentiable hydrology framework
Simultaneous identification of groundwater contamination source and aquifer parameters with a new weighted–average wavelet variable–threshold denoising method
Differential evolution adaptive metropolis sampling method to provide model uncertainty and model selection criteria to determine optimal model for Rayleigh wave dispersion
Inversion and uncertainty of highly parameterized models in a Bayesian framework by sampling the maximal conditional posterior distribution of parameters
Cotton yield prediction with Markov Chain Monte Carlo-based simulation model integrated with genetic programing algorithm: A new hybrid copula-driven approach
Application of tree-ring-based historical growth estimation in ecological process modeling: Dynamic responses of spruce forests in arid regions to climate change
An approximate Bayesian algorithm for training fuzzy cognitive map models of forest responses to deer control in a New Zealand adaptive management experiment
Assessment of future changes in intensity-duration-frequency curves for Southern Ontario using North American (NA)-CORDEX models with nonstationary methods
Using a Bayesian framework and global sensitivity analysis to identify strengths and weaknesses of two process-based models differing in representation of autotrophic respiration
How many sampling points are needed to estimate the mean nitrate-N content of agricultural fields? A geostatistical simulation approach with uncertain variograms
An improved process-based evapotranspiration/heat fluxes remote sensing algorithm based on the Bayesian and Sobol’ uncertainty analysis framework using eddy covariance observations of Tibetan grasslands
Addressing the ill-posedness of multi-layer porous media characterization in impedance tubes through the addition of air gaps behind the sample: Numerical validation
Critical elements for groundwater contamination source identification (GCSI) in sparse/discontinuous data scenarios: Physical constraints and spatiotemporal information
Optimization and uncertainty assessment of strongly nonlinear groundwater models with high parameter dimensionality
showing the first 200 of 576
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