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A python framework for environmental model uncertainty analysis
We have developed pyEMU, a python framework for Environmental Modeling Uncertainty
analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and …
analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and …
Decision support modeling: Data assimilation, uncertainty quantification, and strategic abstraction
J Doherty, C Moore - Groundwater, 2020 - Wiley Online Library
We present a framework for design and deployment of decision support modeling based on
metrics which have their roots in the scientific method. Application of these metrics to …
metrics which have their roots in the scientific method. Application of these metrics to …
Uncertainty assessment and implications for data acquisition in support of integrated hydrologic models
P Brunner, J Doherty… - Water Resources Research, 2012 - Wiley Online Library
The data set used for calibration of regional numerical models which simulate groundwater
flow and vadose zone processes is often dominated by head observations. It is to be …
flow and vadose zone processes is often dominated by head observations. It is to be …
Revisiting “an exercise in groundwater model calibration and prediction” after 30 years: Insights and new directions
In 1988, an important publication moved model calibration and forecasting beyond case
studies and theoretical analysis. It reported on a somewhat idyllic graduate student …
studies and theoretical analysis. It reported on a somewhat idyllic graduate student …
[HTML][HTML] Advances in the pilot point inverse method: Où En Sommes-Nous maintenant?
J White, M Lavenue - Comptes …, 2023 - comptes-rendus.academie-sciences …
Résumé At a conference some years ago, one of the attendees came up to Ghislain de
Marsily and asked,“Excuse me, but aren't you the de Marsily who developed the Pilot Point …
Marsily and asked,“Excuse me, but aren't you the de Marsily who developed the Pilot Point …
Why should practitioners be concerned about predictive uncertainty of groundwater management models?
Numerical models are now commonly used to define guidelines for the sustainable
management of groundwater resources. Despite significant advances in inverse modeling …
management of groundwater resources. Despite significant advances in inverse modeling …
[HTML][HTML] Data space inversion for efficient uncertainty quantification using an integrated surface and sub-surface hydrologic model
It is incumbent on decision-support hydrological modelling to make predictions of uncertain
quantities in a decision-support context. In implementing decision-support modelling, data …
quantities in a decision-support context. In implementing decision-support modelling, data …
Emulator-enabled approximate Bayesian computation (ABC) and uncertainty analysis for computationally expensive groundwater models
Bayesian inference provides a mathematically elegant and robust approach to constrain
numerical model predictions with system knowledge and observations. Technical …
numerical model predictions with system knowledge and observations. Technical …
Case studies of predictive uncertainty quantification for geothermal models
We present case studies on two methods for quantifying uncertainty in predictions for highly
parameterised geothermal models. One method is fully linear, while the other is nonlinear as …
parameterised geothermal models. One method is fully linear, while the other is nonlinear as …
Pathline density distributions in a null‐space Monte Carlo approach to assess groundwater pathways
A null‐space Monte‐Carlo (NSMC) approach was applied to account for uncertainty in the
calibration of the hydraulic conductivity (K) field for a three‐dimensional groundwater flow …
calibration of the hydraulic conductivity (K) field for a three‐dimensional groundwater flow …