John E. Doherty

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The idea that models should be as simple as possible is often accepted without question. However, too much simplification and parsimony may degrade a model's utility. Models are often constructed to make predictions; yet, they are commonly parameterized with a focus on calibration, regardless of whether (1) the calibration data can constrain simulated(More)
Groundwater models can be improved by introduction of additional parameter flexibility and simultaneous use of soft-knowledge. However, these sophisticated approaches have high computational requirements. Cloud computing provides unprecedented access to computing power via the Internet to facilitate the use of these techniques. A modeler can create, launch,(More)
Though popular in the geophysical modeling community, specification of spatially distributed parameters at a scale commensurate with prevailing geological heterogeneity has not been possible in common groundwater modeling practice. The principal reasons for this are (1) the high computational burden of obtaining derivatives necessary for parameter(More)
The values of parameters in a groundwater flow model govern the precision of predictions of future system behavior. Predictive precision, thus, typically depends on an ability to infer values of system properties from historical measurements through calibration. When such data are scarce, or when their information content with respect to parameters that are(More)
Forward with observations Forward with predictions Sensitivity analysis with observations Sensitivity analysis with predictions Parameter estimation with calibration conditions Sensitivity analysis with prediction conditions Simulated values and statistics for observation and prediction sets Simulated values, sensitivities, and statistics for observation(More)
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