% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Beaujean:172070,
author = {Beaujean, J. and Nguyen, F. and Kemna, A. and Antonsson, A.
and Engesgaard, P.},
title = {{C}alibration of seawater intrusion models: {I}nverse
parameter estimation using surface electrical resistivity
tomography and borehole data},
journal = {Water resources research},
volume = {50},
number = {8},
issn = {0043-1397},
address = {Washington, DC},
publisher = {AGU},
reportid = {FZJ-2014-05614},
pages = {6828 - 6849},
year = {2014},
abstract = {Electrical resistivity tomography (ERT) can be used to
constrain seawater intrusion models because of its high
sensitivity to total dissolved solid contents (TDS) in
groundwater and its relatively high lateral coverage.
However, the spatial variability of resolution in electrical
imaging may prevent the correct recovery of the desired
hydrochemical properties such as salt mass fraction. This
paper presents a sequential approach to evaluate the
feasibility of identifying hydraulic conductivity and
dispersivity in density-dependent flow and transport models
from surface ERT-derived mass fraction. In the course of
this study, geophysical inversion was performed by using a
smoothness constraint Tikhonov approach, whereas the
hydrological inversion was performed using a gradient-based
Levenberg-Marquardt algorithm. Two synthetic benchmarks were
tested. They represent a pumping experiment in a homogeneous
and heterogeneous coastal aquifer, respectively. These
simulations demonstrated that only the lower salt mass
fraction of the seawater-freshwater transition zone can be
recovered for different times. This ability has here been
quantified in terms of cumulative sensitivity and our study
has further demonstrated that the mismatch between the
targeted and the recovered salt mass fraction occurs from a
certain threshold. We were additionally able to explore the
capability of sensitivity-filtered ERT images using ground
surface data only to recover (in both synthetic cases) the
hydraulic conductivity while the dispersivity is more
difficult to estimate. We attribute the latter mainly to the
lack of ERT-derived data at depth (where resolution is
poorer) as well as to the smoothing effect of the ERT
inversion.},
cin = {IBG-3},
ddc = {550},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {246 - Modelling and Monitoring Terrestrial Systems: Methods
and Technologies (POF2-246)},
pid = {G:(DE-HGF)POF2-246},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000342632300034},
doi = {10.1002/2013WR014020},
url = {https://juser.fz-juelich.de/record/172070},
}