Premium
Reassessing the MADE direct‐push hydraulic conductivity data using a revised calibration procedure
Author(s) -
Bohling Geoffrey C.,
Liu Gaisheng,
Dietrich Peter,
Butler James J.
Publication year - 2016
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2016wr019008
Subject(s) - calibration , univariate , permeameter , hydraulic conductivity , noise (video) , statistics , confidence interval , environmental science , mathematics , soil science , multivariate statistics , computer science , artificial intelligence , image (mathematics) , soil water
In earlier work, we presented a geostatistical assessment of high‐resolution hydraulic conductivity ( K ) profiles obtained at the MADE site using direct‐push (DP) methods. The profiles are derived from direct‐push injection logger (DPIL) measurements that provide a relative indicator of vertical variations in K with a sample spacing of 1.5 cm. The DPIL profiles are converted to K profiles by calibrating to the results of direct‐push permeameter (DPP) tests performed at selected depths in some of the profiles. Our original calibration used a linear transform that failed to adequately account for an upper limit on DPIL responses in high‐ K zones and noise in the DPIL data. Here we present a revised calibration procedure that accounts for the upper limit and noise, leading to DPIL K values that display a somewhat different univariate distribution and a lower ln K variance (5.9 ± 1.5) than the original calibration values (6.9 ± 1.8), although each variance estimate falls within the other's 95% confidence interval. Despite the change in the univariate distribution, the autocorrelation structure and large‐scale patterns exhibited by the revised DPIL K values still agree well with those exhibited by the flowmeter data from the site. We provide the DPIL and DPP data, along with our calibrated DPIL K values, in the Supporting Information.