Comparison of stochastic and regression based methods for quantification of predictive uncertainty of model-simulated wellhead protection zones in heterogeneous aquifers

Steen Christensen, Catherine Moore, John Doherty

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

For a synthetic case we computed three types of individual prediction intervals for the location of the aquifer entry point of a particle that moves through a heterogeneous aquifer and ends up in a pumping well. (a) The nonlinear regression-based interval (Cooley, 2004) was found to be nearly accurate and required a few hundred model calls to be computed. (b) The linearized regression-based interval (Cooley, 2004) required just over a hundred model calls and also appeared to be nearly correct, (c) The calibration-constrained Monte Carlo interval (Doherty, 2003) was found to be narrower than the regression-based intervals but required about half a million model calls. It is unclear whether or not this type of prediction interval is accurate.

Original languageEnglish
Title of host publicationCalibration and Reliability in Groundwater Modelling
Subtitle of host publicationFrom Uncertainty to Decision Making - Proceedings of ModelCARE 2005
Pages202-208
Number of pages7
Edition304
Publication statusPublished - 2006
Externally publishedYes
EventModelCARE 2005 - Hague, Netherlands
Duration: 6 Jun 20059 Jun 2005

Publication series

NameIAHS-AISH Publication
Number304
ISSN (Print)0144-7815

Conference

ConferenceModelCARE 2005
Country/TerritoryNetherlands
CityHague
Period6/06/059/06/05

Keywords

  • Accuracy
  • Computational requirements
  • Monte Carlo method
  • Prediction interval
  • Predictive uncertainty
  • Regression based method
  • Wellhead protection zone

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