Abstract
Abstract. This paper deals with the issue of monitoring the spatial
distribution of bulk electrical conductivity, σb, in the soil
root zone by using electromagnetic induction (EMI) sensors under different
water and salinity conditions. To deduce the actual distribution of
depth-specific σb from EMI apparent electrical
conductivity (ECa) measurements, we inverted the data by using a
regularized 1-D inversion procedure designed to manage nonlinear multiple
EMI-depth responses. The inversion technique is based on the coupling of the
damped Gauss–Newton method with truncated generalized singular value
decomposition (TGSVD). The ill-posedness of the EMI data inversion is
addressed by using a sharp stabilizer term in the objective function. This
specific stabilizer promotes the reconstruction of blocky targets, thereby
contributing to enhance the spatial resolution of the EMI results in the presence
of sharp boundaries (otherwise smeared out after the application of more
standard Occam-like regularization strategies searching for smooth
solutions). Time-domain reflectometry (TDR) data are used as ground-truth
data for calibration of the inversion results. An experimental field was
divided into four transects 30 m long and 2.8 m wide, cultivated with green
bean, and irrigated
with water at two different salinity levels and using two
different irrigation volumes. Clearly, this induces different salinity and
water contents within the soil profiles. For each transect, 26 regularly
spaced monitoring soundings (1 m apart) were selected
for the collection of (i) Geonics EM-38 and (ii) Tektronix reflectometer data.
Despite the original discrepancies in the EMI and TDR data, we found a
significant correlation of the means and standard deviations of the two data
series; in particular, after a low-pass spatial filtering of the TDR data.
Based on these findings, this paper introduces a novel methodology to
calibrate EMI-based electrical conductivities via TDR direct measurements.
This calibration strategy consists of a linear mapping of the original
inversion results into a new conductivity spatial distribution with the
coefficients of the transformation uniquely based on the statistics of the
two original measurement datasets (EMI and TDR conductivities).
Subject
General Earth and Planetary Sciences,General Engineering,General Environmental Science
Cited by
26 articles.
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