HR: 08:45h
AN: H11I-03    [Abstracts]
TI: Inference of 3-D Hydraulic Conductivity from Flowmeter and Pumping-Test Data
AU: * Li, W
EM: wei.li@eawag.ch
AF: Swiss Federal Institute of Aquatic Science and Technology (Eawag), Überlandstr. 133, Dübendorf, 8600, Switzerland
AU: Englert, A
EM: alenglert@lbl.gov
AF: Lawrence Berkeley National Laboratory, Dept. of Earth Sciences, Cyclotron Road, Berkeley, CA 94720, United States
AU: Vereecken, H
EM: h.vereecken@fz-juelich.de
AF: ICG-IV, Agrosphere Institute, Forschungszentrum Jülich, Jülich, 52425, Germany
AU: Cirpka, O A
EM: olaf.cirpka@eawag.ch
AF: Swiss Federal Institute of Aquatic Science and Technology (Eawag), Überlandstr. 133, Dübendorf, 8600, Switzerland
AB: We jointly apply field data of flowmeter and multiple pumping tests in fully screened wells to estimate hydraulic conductivity using a geostatistical inversion method. We use the steady state drawdowns of pumping tests and the discharge profiles of flowmeter tests as our data in the inference. The discharge profiles are not converted to "measurements" of hydraulic conductivities. The flowmeter profiles are indicative of the relative vertical distribution of hydraulic conductivity in the direct vicinity of the boreholes, while drawdown measurements of pumping tests provide information about horizontal fluctuation of the depth-averaged hydraulic conductivity. For inversion, we use the quasi-linear geostatistical approach of Kitanidis (1995), accelerated by spectral methods for the evaluation of cross-covariance matrices (Nowak et al., 2003) and stabilized by a modified Levenberg-Marquardt method (Nowak and Cirpka, 2004). We apply the method to data obtained at the Krauthausen test site of the research center Jülich, Germany. In the field, multiple pumping tests were conducted in a hydraulic tomographic format, stressing and monitoring the aquifer at different locations. We determine the most likely estimate of hydraulic conductivity and the associated posterior uncertainty. The resulting estimate of our joint three-dimensional geostatistical inversion shows an improved three-dimensional structure in comparison to the inversion of pumping test data only. The corresponding uncertainty field shows a considerable decrease near the wells where both tests were conducted.
DE: 1829 Groundwater hydrology
DE: 1869 Stochastic hydrology
DE: 3260 Inverse theory
SC: Hydrology [H]
MN: 2007 Fall Meeting