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HydrogeoSieveXL: an Excel-based tool to estimate hydraulic conductivity from grain-size analysis

For over a century, hydrogeologists have estimated hydraulic conductivity ( K ) from grain-size distribution curves. The benefits of the practice are simplicity, cost, and a means of identifying spatial variations in K . Many techniques have been developed over the years, but all suffer from similar...

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Bibliographic Details
Published in:Hydrogeology journal 2015-06, Vol.23 (4), p.837-844
Main Author: Devlin, J. F.
Format: Article
Language:English
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Summary:For over a century, hydrogeologists have estimated hydraulic conductivity ( K ) from grain-size distribution curves. The benefits of the practice are simplicity, cost, and a means of identifying spatial variations in K . Many techniques have been developed over the years, but all suffer from similar shortcomings: no accounting of heterogeneity within samples (i.e., aquifer structure is lost), loss of grain packing characteristics, and failure to account for the effects of overburden pressure on K . In addition, K estimates can vary by an order of magnitude between the various methods, and it is not generally possible to identify the best method for a given sample. The drawbacks are serious, but the advantages have seen the use of grain-size distribution curves for K estimation continue, often using a single selected method to estimate K in a given project. In most cases, this restriction results from convenience. It is proposed here that extending the analysis to include several methods would be beneficial since it would provide a better indication of the range of K that might apply. To overcome the convenience limitation, an Excel-based spreadsheet program, HydrogeoSieveXL, is introduced here. HydrogeoSieveXL is a freely available program that calculates K from grain-size distribution curves using 15 different methods. HydrogeoSieveXL was found to calculate K values essentially identical to those reported in the literature, using the published grain-size distribution curves.
ISSN:1431-2174
1435-0157
DOI:10.1007/s10040-015-1255-0