Uncertainty quantification for stream depletion tests

Tiangang Cui, Nicholas Dudley Ward

Research output: Contribution to journalArticleResearchpeer-review

6 Citations (Scopus)


This study considers the problem of quantifying stream depletion from pumping test data. Bayesian inference is used to quantify the posterior uncertainty of parameters for a simple vertically heterogeneous aquifer model, in which the pumped semiconfined aquifer is separated by an aquiclude from a phreatic aquifer hydraulically connected to a stream. This study investigates the effects of using different data sets and shows that a single pumping test is generally not sufficient to determine stream depletion within reasonable limits. However, uncertainty quantification conducted within a Bayesian context reveals that by judicious design of aquifer tests, stream depletion can be accurately determined from data.

Original languageEnglish
Pages (from-to)1581-1590
Number of pages10
JournalJournal of Hydrologic Engineering
Issue number12
Publication statusPublished - 2013
Externally publishedYes


  • Bayesian inference
  • Groundwater
  • Markov chain Monte Carlo
  • Parameter estimation
  • Pumping tests
  • Stream depletion
  • Uncertainty quantification

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