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Müller S, Leven C, Dietrich P, et al. How to Find Aquifer Statistics Utilizing Pumping Tests? Two Field Studies Using welltestpy. Ground Water. 2021;60(1):137-144doi: 10.1111/gwat.13121.
Müller, S., Leven, C., Dietrich, P., Attinger, S., & Zech, A. (2022). How to Find Aquifer Statistics Utilizing Pumping Tests? Two Field Studies Using welltestpy. Ground water, 60(1), 137-144. https://doi.org/10.1111/gwat.13121
Müller, Sebastian, et al. "How to Find Aquifer Statistics Utilizing Pumping Tests? Two Field Studies Using welltestpy." Ground water vol. 60,1 (2022): 137-144. doi: https://doi.org/10.1111/gwat.13121
Müller S, Leven C, Dietrich P, Attinger S, Zech A. How to Find Aquifer Statistics Utilizing Pumping Tests? Two Field Studies Using welltestpy. Ground Water. 2022 Jan;60(1):137-144. doi: 10.1111/gwat.13121. Epub 2021 Jul 14. PMID: 34231221.
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Ground Water. 2022 Jan;60(1):137-144. doi: 10.1111/gwat.13121. Epub 2021 Jul 14.

How to Find Aquifer Statistics Utilizing Pumping Tests? Two Field Studies Using welltestpy.

Ground water

Sebastian Müller, Carsten Leven, Peter Dietrich, Sabine Attinger, Alraune Zech

Affiliations

  1. Helmholtz Centre for Environmental Research (UFZ), 04318, Leipzig, Germany.
  2. Institute of Environmental Science and Geography, University of Potsdam, 14476, Potsdam, Germany.
  3. Department of Geoscience, University of Tübingen, 72074, Tübingen, Germany.
  4. Department of Earth Science, Utrecht University, 3584, CS, Utrecht, The Netherlands.

PMID: 34231221 DOI: 10.1111/gwat.13121

Abstract

We present a workflow to estimate geostatistical aquifer parameters from pumping test data using the Python package welltestpy. The procedure of pumping test analysis is exemplified for two data sets from the Horkheimer Insel site and from the Lauswiesen site, Germany. The analysis is based on a semi-analytical drawdown solution from the upscaling approach Radial Coarse Graining, which enables to infer log-transmissivity variance and horizontal correlation length, beside mean transmissivity, and storativity, from pumping test data. We estimate these parameters of aquifer heterogeneity from type-curve analysis and determine their sensitivity. This procedure, implemented in welltestpy, is a template for analyzing any pumping test. It goes beyond the possibilities of standard methods, for example, based on Theis' equation, which are limited to mean transmissivity and storativity. A sensitivity study showed the impact of observation well positions on the parameter estimation quality. The insights of this study help to optimize future test setups for geostatistical aquifer analysis and provides guidance for investigating pumping tests with regard to aquifer statistics using the open-source software package welltestpy.

© 2021 The Authors. Groundwater published by Wiley Periodicals LLC on behalf of National Ground Water Association.

References

  1. Bear, J. 1972. Dynamics of Fluids in Porous Media. New York: Elsevier. - PubMed
  2. Dagan, G. 1989. Flow and Transport in Porous Formations. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-75015-1 - PubMed
  3. Duan, Q., S. Sorooshian, and V. Gupta. 1992. Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resources Research 28, no. 4: 1015-1031. https://doi.org/10.1029/91WR02985 - PubMed
  4. Fiori, A., V. Cvetkovic, G. Dagan, S. Attinger, A. Bellin, P. Dietrich, A. Zech, and G. Teutsch. 2016. Debates - Stochastic subsurface hydrology from theory to practice: The relevance of stochastic subsurface hydrology to practical problems of contaminant transport and remediation. What is characterization and stochastic theory good for? Water Resources Research 52, no. 12: 9228-9234. https://doi.org/10.1002/2015WR017525 - PubMed
  5. Gelhar, L.W. 1993. Stochastic Subsurface Hydrology. New York: Prentice Hall, Englewood Cliffs. - PubMed
  6. Houska, T., P. Kraft, A. Chamorro-Chavez, and L. Breuer. 2015. SPOTting model parameters using a ready-made python package. PLoS ONE 10, no. 12: e0145180. https://doi.org/10.1371/journal.pone.0145180 - PubMed
  7. Indelman, P., and B. Abramovich. 1994. Nonlocal properties of nonuniform averaged flows in heterogeneous media. Water Resources Research 30, no. 12: 3385-3393. https://doi.org/10.1029/94WR01782 - PubMed
  8. Lessoff, S.C., U. Schneidewind, C. Leven, P. Blum, P. Dietrich, and G. Dagan. 2010. Spatial characterization of the hydraulic conductivity using direct-push injection logging. Water Resources Research 46, no. 12: W12502. https://doi.org/10.1029/2009WR008949 - PubMed
  9. Leven, C. 2020. Pumping Tests in Wells B1-B5 at the Hydrogeological Research Site Lauswiesen. Tübingen: Eberhard Karls Universität Tübingen http://hdl.handle.net/10900.1/bfb0b0f7-7065-4a24-8a91-92ad8aa8fc40. - PubMed
  10. Leven, C., and P. Dietrich. 2006. What information can we get from pumping tests? Comparing pumping test configurations using sensitivity coefficients. Journal of Hydrology 319: 199-215. https://doi.org/10.1016/j.jhydrol.2005.06.030 - PubMed
  11. Müller, S. 2021. GeoStat-Framework/welltestpy: v1.0.3. Zenodo. https://doi.org/10.5281/zenodo.4549297 (accessed February 19, 2021). - PubMed
  12. Müller, S. 2020. GeoStat-Framework/AnaFlow v1.0.1. Zenodo. https://doi.org/10.5281/zenodo.3738268 (accessed May 31, 2020). - PubMed
  13. Müller, S., and A. Zech. 2021. GeoStat-Examples/welltestpy-field-site-analysis: v1.1.0. Zenodo. https://doi.org/10.5281/zenodo.4724118 (accessed April 27, 2021). - PubMed
  14. Neuman, S.P., A. Guadagnini, and M. Riva. 2004. Type-curve estimation of statistical heterogeneity. Water Resources Research 40: W04201. https://doi.org/10.1029/2003WR002405 - PubMed
  15. Rajaram, H. 2016. Debates-Stochastic subsurface hydrology from theory to practice: Introduction. Water Resources Research 52, no. 12: 9215-9217. https://doi.org/10.1002/2016WR020066 - PubMed
  16. Riva, M., L. Guadagnini, A. Guadagnini, T. Ptak, and E. Martac. 2006. Probabilistic study of well capture zones distribution at the Lauswiesen field site. Journal of Contaminant Hydrology 88, no. 1: 92-118. https://doi.org/10.1016/j.jconhyd.2006.06.005 - PubMed
  17. Saltelli, A., S. Tarantola, and K.P.-S. Chan. 1999. A quantitative model-independent method for global sensitivity analysis of model output. Technometrics 41, no. 1: 39-56. https://doi.org/10.1080/00401706.1999.10485594 - PubMed
  18. Sánchez-Vila, X., A. Guadagnini, and J. Carrera. 2006. Representative hydraulic conductivities in saturated groundwater flow. Reviews of Geophysics 44: RG3002. https://doi.org/10.1029/2005RG000169 - PubMed
  19. Schad, H. 1997. Variability of hydraulic parameters in non-uniform porous media: Experiments and stochastic modeling at different scales. PhD thesis, University Tübingen. - PubMed
  20. Schad, H., and G. Teutsch. 1994. Effects of the investigation scale on pumping test results in heterogeneous porous aquifers. Journal of Hydrology 159: 61-77. https://doi.org/10.1016/0022-1694(94)90249-6 - PubMed
  21. Zech, A., S. Müller, J. Mai, F. Heße, and S. Attinger. 2016. Extending Theis' solution: Using transient pumping tests to estimate parameters of aquifer heterogeneity. Water Resources Research 52, no. 8: 6156-6170. https://doi.org/10.1002/2015WR018509 - PubMed
  22. Zech, A., and S. Attinger. 2015. Technical note: Analytical solution for the mean drawdown of steady state pumping tests in two-dimensional isotropic heterogeneous aquifers. Hydrology and Earth System Sciences 12: 6921-6944. https://doi.org/10.5194/hessd-12-6921-2015 - PubMed
  23. Zech, A., C.L. Schneider, and S. Attinger. 2012. The extended Thiem's solution-Including the impact of heterogeneity. Water Resources Research 48, no. 10: W10535. https://doi.org/10.1029/2012WR011852 - PubMed

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