Characterizing the spatial variability of transmissivity using stochastic type-curve and numerical inverse analyses of data from a sequence of pumping tests

Monica Riva, Alberto Guadagnini, Shlomo P. Neuman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We discuss two recent methods of characterizing the spatial variability of a random (natural) log transmissivity field on the basis of observed space-time variations in hydraulic head: a graphical stochastic type-curve method and a geostatistical method of inverting (ensemble) mean flow equations. While both methods allow estimating the unconditional variance and integral (correlation) scale of log transmissivities, geostatistical inversion is computationally more intensive, but also provides tomographic images of how log transmissivity estimates and their variance vary in space. We apply the two approaches to synthetic scenarios and to measured late time (quasi-steady state) drawdowns from a sequence of transient pumping tests in an unconfined aquifer near Tübingen, Germany.

Original languageEnglish (US)
Title of host publicationProceedings of an International Conference on Calibration and Reliability in Groundwater Modelling
Subtitle of host publicationCredibility of Modelling, ModelCARE2007
Pages39-44
Number of pages6
Edition320
StatePublished - Nov 7 2008
EventInternational Conference on Calibration and Reliability in Groundwater Modelling: Credibility of Modelling, ModelCARE2007 - Copenhagen, Denmark
Duration: Sep 9 2007Sep 13 2007

Publication series

NameIAHS-AISH Publication
Number320
ISSN (Print)0144-7815

Other

OtherInternational Conference on Calibration and Reliability in Groundwater Modelling: Credibility of Modelling, ModelCARE2007
CountryDenmark
CityCopenhagen
Period9/9/079/13/07

Keywords

  • Geostatistics
  • Pumping tests
  • Stochastic inverse models
  • Type curves

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

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