Uncertainty Quantification for Stream Depletion Tests

Abstract

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.