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\DOI{10.5802/crgeos.291}
\datereceived{2025-01-16}
\dateaccepted{2025-04-08}
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\dateposted{2025-04-29}
\begin{document}

\begin{noXML}

\TopicFR{Hydrologie, hydrog\'eologie}
\TopicEN{Hydrology, hydrogeology}
\TopicFR{G\'eophysique de surface}
\TopicEN{Surface geophysics}

\CDRsetmeta{articletype}{research-article}

\shortrunauthors

\title{Advances in agrogeophysics: geophysical monitoring of the
fresh--saline water interface in an agricultural field in the Belgian
polders}

\alttitle{Progr\`es en agrog\'eophysique : suivi g\'eophysique de l'interface
eau douce-eau sal\'ee dans un champ agricole des polders belges}

\author{\firstname{Guillaume} \lastname{Blanchy}\CDRorcid{0000-0001-6341-5826}\IsCorresp}
\address{University of Li\`ege (ULi\`ege), Urban and Environmental Engineering, Li\`ege, Belgium}
\address{F.R.S.-FNRS (Fonds de la Recherche Scientifique), Brussels, Belgium}
\email[G. Blanchy]{gblanchy@uliege.be}

\author{\firstname{Bert} \lastname{Everaert}\CDRorcid{0009-0003-0259-0024}}
\address{Inagro, Department of Soil, Water and Fertilisation, Roeselare, Belgium}

\author{\firstname{Erika}  \lastname{Rodriguez}\CDRorcid{0009-0005-1550-0950}}
\address{Flanders Research Institute for Agriculture, Fisheries and
Food (ILVO), Plant Sciences Unit, Melle, Belgium}

\author{\firstname{Ali}\nobreakauthor\lastname{Mehmandoostkotlar}\CDRorcid{0000-0002-3000-5983}}
\addressSameAs{4}{Flanders Research Institute for Agriculture,
Fisheries and Food (ILVO), Plant Sciences Unit, Melle, Belgium}

\author{\firstname{David} \lastname{Caterina}\CDRorcid{0000-0002-1695-4779}}
\addressSameAs{1}{University of Li\`ege (ULi\`ege), Urban and Environmental
Engineering, Li\`ege, Belgium}

\author{\firstname{Jonathan} \lastname{Chambers}\CDRorcid{0000-0002-8135-776X}}
\address{British Geological Survey (BGS), Geophysical Tomography Team,
Nottingham, UK}

\author{\firstname{Fr\'ed\'eric}\nobreakauthor\lastname{Nguyen}\CDRorcid{0000-0002-6332-7815}}
\addressSameAs{1}{University of Li\`ege (ULi\`ege), Urban and Environmental
Engineering, Li\`ege, Belgium}

\author{\firstname{Thomas} \lastname{Hermans}\CDRorcid{0000-0001-9522-1540}}
\address{University of Ghent (UGent), Department of Geology, Ghent,
Belgium}

\author{\firstname{Philippe} \lastname{De Smedt}\CDRorcid{0000-0002-7230-4965}}
\address{University of Ghent (UGent), Department of Environment, Ghent, Belgium}

\author{\firstname{Dominique} \lastname{Huits}\CDRorcid{0000-0001-7487-6767}}
\addressSameAs{3}{Inagro, Department of Soil, Water and Fertilisation, Roeselare, Belgium}

\author{\firstname{Sarah}\nobreakauthor\lastname{Garr\'e}\CDRorcid{0000-0001-9025-5282}}
\address{KULeuven, Soil and Water Management Unit, Leuven, Belgium}
\addressSameAs{4}{Flanders Research Institute for Agriculture,
Fisheries and Food (ILVO), Plant Sciences Unit, Melle, Belgium}

\thanks{Fonds de la Recherche Scientifique---FNRS (CR: 1.B.044.22F),
Flemish Government (VLAIO HBC.2020.3159).}


\begin{abstract} 
Polders are coastal low-lying areas reclaimed on the sea mainly for
agriculture. They are constantly drained by pumps, ditches and
subsurface drains. In West-Flanders, Belgium they are composed of a
shallow freshwater lens on top of denser saline groundwater. This
freshwater lens is essential for crop growth but during dry periods, it
can disappear and the saline groundwater can enter the root zone by
capillary rise and endanger yield. To prevent this, farmers can use
controlled drainage to raise the water table in their field during
winter months to increase the freshwater lens thickness. To study the
effectiveness of the technique, we monitored three fields with
piezometers, resistivity sticks alongside field mapping using
electromagnetic induction for three years. The resistivity sticks
highlighted lithological differences, but also enabled us to monitor
the fresh--saline water interface and the water table accurately.
Controlled drainage retained additional rainfall during intense summer
precipitation but little effect was observed on the fresh--saline water
interface. Soil heterogeneity and past land use of the field seem to
have a larger effect on the fresh--saline water interface. Despite the
limited effect on the freshwater lens, the value of geophysical methods
for monitoring its thickness for field-scale study was demonstrated.
\end{abstract}

\begin{altabstract} 
Les polders sont des zones gagn\'ees sur la mer, principalement pour
l'agriculture. Ils sont constamment drain\'es. En Flandre occidentale, en
Belgique, ils sont constitu\'es d'une lentille d'eau douce peu profonde
sur une nappe phr\'eatique saline. Cette lentille d'eau douce est
essentielle \`a la croissance des cultures, mais pendant les p\'eriodes
s\`eches, elle peut dispara\^itre et l'eau saline peut remont\'e jusqu'aux
racines et compromettre le rendement. Pour \'eviter cela, les
agriculteurs peuvent utiliser le drainage contr\^ol\'e afin d'augmenter
l'\'epaisseur de la lentille d'eau douce. Pour \'etudier l'efficacit\'e de
cette technique, nous avons suivi trois champs \`a l'aide de pi\'ezom\`etres,
de sondes de r\'esistivit\'e et d'une cartographie par induction
\'electromagn\'etique pendant trois ans. Ces techniques ont mis en \'evidence
les diff\'erences lithologiques et ont \'egalement permis de surveiller
avec pr\'ecision l'interface eau douce-eau sal\'ee et le niveau de la nappe
phr\'eatique. Le drainage contr\^ol\'e a permis de retenir des pr\'ecipitations
suppl\'ementaires pendant les fortes pr\'ecipitations estivales, mais peu
d'effets ont \'et\'e observ\'es sur l'interface eau douce-eau sal\'ee.
L'h\'et\'erog\'en\'eit\'e du sol et son utilisation ant\'erieure semblent avoir un
effet plus important. Malgr\'e cela, la pertinence des m\'ethodes
g\'eophysiques pour suivre l'\'epaisseur de la lentille d'eau douce \`a
l'\'echelle du champ a \'et\'e d\'emontr\'ee.
\end{altabstract} 

\keywords{\kwd{Salinity}
\kwd{Polder}
\kwd{Agrogeophysics}
\kwd{Hydrogeophysics}
\kwd{Controlled drainage}
\kwd{Electrical resistivity tomography}
\kwd{Frequency-domain electromagnetic induction}}

\altkeywords{\kwd{Salinit\'e}
\kwd{Polder}
\kwd{Agrog\'eophysique}
\kwd{Hydrogeophysique}
\kwd{Drainage contr\^ol\'e}
\kwd{Tomographie de resistivit\'e \'electrique}
\kwd{Induction electromagn\'etique dans le domaine fr\'equentiel}}

\maketitle

\twocolumngrid

\end{noXML}

\let\rmmu\upmu

\section{Introduction}\label{sec1}

Polders are low-lying coastal areas that used to be submerged at high
tides. Progressively, dikes have been erected to prevent transgression
from the sea and a network of ditches established to drain the land,
making it suitable for agricultural activities. Polders can be found in
the North of Belgium but also in the Netherlands, north-west of
Germany, UK and in several other parts of the world. Originally,
ditches were used to drain the land effectively. From the 1950,
subsurface drains, initially ceramic, and more recently plastic, were
buried in agricultural fields to improve the drainage, also in more
sloping land \citet{ritzema_drainage_1994}. This led to larger field
sizes that could be easily cultivated by agricultural machinery. These
subsurface drains, also called tile-drains, are a very common
agricultural improvement technique \citep{castellano_sustainable_2019}.
They bring the collected water from the field to its surrounding
ditches. Within a polder, the water level in ditches is managed by a
water board. They remove excess water by releasing it to the sea at
low-tide either by gravity or by pumping. Drainage in the polder is
essential to avoid flooding and keep the land dry enough for
agricultural \unskip\break activity.

In the polders, the groundwater table is shallow (typically 1 or 2 m
deep during winter time). In the Belgian polders, the groundwater is
often saline or brackish. It does not come from present seawater
intrusion, as the dunes at the coast form a freshwater protection
\citep{hermans_imaging_2012, delsman_topsoil_2019}. This saline water
is connate water from the time when the polder areas were still under
marine influence. Owing to the extensive drainage and relatively low
permeability of the sediments, this water has not been fully freshened
yet. Nevertheless, with time, freshwater lenses develop on top of the
denser saline water due to recharge. The thickness of these lenses can
vary from a few meters to tens of meters mostly depending on the
geology of the area. For instance, sandy areas (such as creek ridges)
tend to be fresher as they infiltrate more rainwater than clay-rich
areas; hence they can be used to store freshwater
\citep{pauw_field_2015}. The thickness of freshwater lenses also vary
throughout the season \citep{de_louw_saline_2013,eeman_dynamics_2017}.
Recharge occurs during winter months from December to March; while in
summer, the thickness of the freshwater lenses decreases due to root
water uptake by the crops and soil evaporation. In some circumstances,
for instance during drought, freshwater lenses can be completely
consumed, leaving place to brackish saline water that can potentially
reach the root zone by capillary forces, endangering yield
\citep{velstra_observations_2011, fao_global_2024}. Capillary rise of
brackish saline groundwater is not the only process that can lead to
salinization of coastal areas
\citep{daliakopoulos_threat_2016,fao_global_2024}.  However, it is a
major concern for lowland regions that are projected to be home to 1400
million people by 2060 \citep{neumann_future_2015}. Hence, smart
drainage management is essential to maintain the freshwater lens intact
and buffer intense precipitation \citep{ritzema_drain_2016}.

Controlled drainage, or the use of controllable retaining structures to
adjust the drainage level, is one solution that enables drainage
management. In fields where all subsurface drains are connected to a
collector drain, one can adjust the drainage level of the entire field
by adjusting the outflow level of the collector drain in a control pit.
At the polder scale, water boards can also adjust the level of water in
the network of ditches by opening or closing gates connected to the sea
or inland waterways. The water board often increases the water level in
the ditches in the summer by bringing freshwater from inland waterways,
originally to provide sufficient water for agricultural activities
(e.g.\ grazing livestock) and more recently to prevent drought-induced
salinization. While we acknowledge the importance of this collective
behaviour, in this manuscript, we focus on the drainage management of
subsurface drains at the field scale. While this is the scale at which
individual farmers can intervene, such systems equally interact with
ditches in the wider area that are separately managed.

Besides salinization prevention, controlled drainage can also be
helpful for (sub)irrigation \citep{ayars_controlled_2006,
de_wit_controlled_2024}, improving water quality
\citep{evans_controlled_1995, dou_evaluating_2023} or other ecosystem
services such as providing wetland habitats or pesticide retention
\citep{mitchell_review_2023}. The management of controlled drainage
(level \mbox{applied} and duration) is also an active area of research 
(e.g.\ \xcitealp{rodriguez_performance_2024}{2024}; 
\xcitealp{de_wit_hydrological_2024}{2024} or
\xcitealp{salla_simulating_2024}{2024}). Nonetheless, the advantage of
controlled drainage in terms of crop yield remains unclear with little
\citep{elsen_drainage_2019} or no benefit \citep{youssef_impact_2023,
wang_effects_2020}. In this study, we will mainly focus on the effect
of controlled drainage on salinization.

Geophysical techniques have been widely used to map salinity in the
polder context 
\citep{deleersnyder_flexible_2023,de_louw_topsoil_2019,hermans_imaging_2012,
vandenbohede_flow_2011}. The increase in
electrical conductivity due to saline water offers a strong contrast
for electrical and electromagnetic techniques. Electrical monitoring
systems such as the salt water monitoring system (SAMOS)
\citep{ronczka_monitoring_2020} have even been developed to monitor the
fresh--saline water interface over a long period of time. Similarly,
\citet{paepen_footprint_2023} demonstrated how surface electrical
resistivity tomography (ERT) can be used to map the boundary of fresh
and saline water at the coast and investigated submarine groundwater
discharge. In Belgium, mapping of the depth to the saline water in the
polders was first obtained thanks to vertical electrical sounding (VES)
by
\citet{de_breuck_evolution_1974} and later using helicopter-born
time-domain electromagnetic (TEM) survey
\citep{delsman_large-scale_2018,delsman_topsoil_2019}. While these
maps are useful to identify sites more sensitive to saline groundwater,
their vertical resolution (metric resolution) remains too coarse to
monitor the effect of specific agronomic measures at field scale.

While geophysical techniques were used at regional scale to map the
depth to saline water, fewer studies used them at the field-scale in
combination with agricultural subsurface drainage.
\citet{velstra_observations_2011} uses surface ERT to show the
complexity and the dynamics of fresh and saline groundwater in clayey
polders and their interaction with subsurface drains. They observed the
seasonal dynamics described above while acknowledging the challenge of
separating unsaturated (fresh or saline), saturated fresh and saturated
saline regions. \citet{delsman_investigating_2014} uses ERT and
electromagnetic induction (EMI) to study the effect of exfiltration of
salts through ditches. They found that most groundwater salts (80\%)
are discharged through the subsurface drains and only a fraction is
exfiltrated by the ditches. Both fluxes are influenced by precipitation
and regional groundwater level respectively. In this work, the effect
of controlled drainage as a field-scale measure to prevent salinization
and store more freshwater is studied. The use of geophysical methods
aims to extrapolate point-like information from piezometers and
characterize the heterogeneity of these complex artificial systems.
Overall, the study aims to estimate the value of geophysical techniques
(ERT or EMI) for delineating the interface between saline and fresh
water with and without controlled drainage.

\section{Materials and methods}
\subsection{Experimental site}
The site is composed of three fields (CD, RD and ND) located within a
farm in the North West of Belgium (51.139~N, 2.814~E). The site is
located in the Middenkust polder and the water level in the ditches
surrounding the field are managed by their water board
(\url{https://www.middenkustpolder.be/}, accessed on 2024-11-19).  This
location was chosen based on the shallow saline water boundary (${&lt;}$2~m
below surface) determined from the optimistic salinity map (DOV). It
has also been selected as the similar drainage, soil type and the
proximity of the fields enable easier statistical comparison.
Figure~\ref{fig:plan} shows the general setup of the field, the location
of the subsurface drains (0.9~m depth at the outlet with a slope of 
0.1\%). CD and RD fields have a surface of 2 ha while ND field is about 
1~ha. In both CD and RD fields, the south--north tile drains are connected
to a collector drain that goes to the ditch. The water level in the CD
and RD fields can be adjusted at the outlet of the collector drain
thanks to an elbow and a set of pipes of different heights. The
west--east tile drains of ND field go directly to the ditch. Each field
is equipped with an ultrasonic flowmeter (ElecTo Bulk DN 65, Maddalena
equipped with a logger from Crodeon, Ghent, Belgium) to monitor the
amount of water drained. In the ND field, the outflow of two adjacent
tile drains is collected to estimate the discharge from the field. In
each field, three locations (e.g.\ CD1, CD2 and CD3 for CD field) are
equipped with piezometers, soil moisture sensors and ERT sticks. For CD
and RD, location 1 (CD1, RD1) is the closest to the drainage outlet
while location 3 (CD3, RD3) is the furthest. The dominant soil type of
all three fields is a Fluvisol (WRB 2006). A weather station was
installed in the lower South East corner of the ND field to record
local precipitation, wind and solar radiation. Daily potential soil
moisture deficit (PSMD) was computed as the cumulated potential
evapotranspiration (Penman-Monteith, penmon v1.5 Python package) minus
the precipitation. Remote sensing satellite pictures from Sentinel 2
(Terrascope 2024) were used to compute median normalised difference
vegetation index (NDVI) measurements per field.

\begin{figure}
\includegraphics{fig01}
\vspace*{-3pt}
\caption{\label{fig:plan}Overview of the experimental site in
Middelkerke (Belgium) with three fields equipped (CD, RD and ND). In
each field, three locations are monitored (e.g.\ RD1, RD2, RD3). The
drainage system (PVC drains at about 0.9~m depth, spaced 8 m with an
average slope of 0.1\%) are visible in cyan. In the CD and RD field,
the south--north drains are merged into a collector drain and brought to
a control pit where an elbow can adjust the water table. Blue dots
denote outlet of drainage pipes (or control pit) in the polder-managed
ditch (dark blue).} 
\vspace*{-4pt} 
\end{figure}

\begin{figure*}
\vspace*{-1pt}
\includegraphics{fig02}
\vspace*{-1pt}
\caption{\label{fig:lithology}Each location is equipped with three
piezometers with depths of 1.5, 2 and 3 m (with screen length of 0.5 m
at the bottom of the piezometer). In addition, an ERT stick with 16
electrodes spaced of 0.15 m with first electrodes starting at 0.8 m
depth is placed next to the piezometers. The different soil layers that
have been observed while installing the piezometer are also shown. The
raw EC$_{\mathrm{a}}$ collected from the Wenner array is shown on the
right of the profile (the depth is the midpoint of the quadrupole). The
dashed vertical grey line shows the 230 mS/m threshold.}
\vspace*{-2pt}
\end{figure*}


\subsection{Instrumentation}
Within each field, three locations were monitored. At each location,
three piezometers were placed up to depths of 1.5, 2 and 3 m below
surface from North to South, spaced 0.5 m (Figure~\ref{fig:lithology}).
The piezometers have a screen on the bottom 0.5 m. The top 1~m part of
the piezometer (from ${-}$0.5 to 0.5~m above surface) can be removed which
enables us to bury the piezometer when large machinery for ploughing,
sowing or harvesting needs to go on the field. Water samples from all
piezometers were collected monthly and measured with a general lab
conductivity meter and a Na+ specific sensor (LAQUAtwin-Na-11, Horiba,
Japan). The deepest piezometer of each location (e.g.\ CD1-300) was
equipped with a CTD diver (Van Essen Instruments, Waterloo, Canada) or
a DL-CTD10 (Decentlab, D\"ubendorf, Switzerland) to \mbox{measure} pressure,
temperature and electrical conductivity (EC). The pressure data were
corrected for barometric pressure variations to obtain raw water heads.
Given that the density of saline water is larger than the density of
freshwater, the same pressure at the sensor can be linked to different
heads of water above it. Hence, the raw water heads were then corrected
to freshwater heads based on the electrical conductivity observed 
\citep[e.g.][]{vandenbohede_salt_2008}. 
The difference between raw water heads
and corrected freshwater heads was less than 0.015~m. From manual
augering, different soil layers were identified from top to bottom:
first an Ap layer used for agricultural activities, then a consolidated
clay layer with traces of rust, then unconsolidated (unripened) clay
(i.e.\ clay that was always under the water table, that never
consolidated or ripened in unsaturated condition) were found. In some
locations, peat layers were found. In addition to the piezometers, each
location is also equipped with an ERT stick with 16 ring electrodes,
spaced 0.15 m with the first electrode at 3.05 m depth and the last at
0.8 m depth below surface. The sticks in CD and RD fields have a
diameter of 0.05 m, stainless steel electrodes rings internally
connected. Spacers between rings are made of plastic and screw into
each other. This modular design enables us to build a stick of the
desired length. The sticks in the ND field are built around a bamboo
stick of 0.015~m diameter. The electrodes are made with the last 0.3 m
naked extremities of the cable (tinned copper) coiled and soldered on
top of aluminium foil to increase contact area. This design, while less
robust, is cheaper and similar data quality (reciprocal error, stacking
error, contact resistances) is observed for both types of sticks. A
Wenner sequence where potential electrodes are between the current
electrodes, all four electrodes equally spaced was used. This sequence
was acquired monthly with a Syscal Pro 120 (Iris Instrument, Orl\'eans,
France). A PRIME geoelectrical monitoring system 
\citep[e.g.][]{chambers_long-term_2022} was also used to monitor the sticks in
CD1 and CD2 daily with the same sequence. Figure~\ref{fig:lithology}
shows the apparent electrical conductivity (EC$_{\mathrm{a}}$) derived from the ERT
readings along the sticks. The EC$_{\mathrm{a}}$ increases with depth and this
increase is often associated with the presence of peat. Locations
without peat in the first 3 m (like RD3) show a lower EC$_{\mathrm{a}}$ value.
Time-domain transmission soil moisture sensors (TMS-4, TOMST,
\citet{wild_climate_2019}) were \mbox{installed} at depth of 0.15, 0.3 and
0.45 m at all CD and RD locations and in ND1. These sensors were also
installed at 1, 1.5 and 2 m to measure soil temperature variation.
Frequency domain electromagnetic induction (EMI) data were collected
using a DUALEM-421S (Dualem Inc., Canada) that can measure up to 6
{different} coil configurations: PRP1.1 (perpendicular \mbox{orientation} with
1.1~m between \mbox{transmitter} and \mbox{receiver} coil), PRP2.1, PRP4.1, HCP1
(horizontal coplanar orientation), HCP2 and HCP4.

\begin{figure*}
\includegraphics{fig03}
{\vspace*{1pt}}
\caption{\label{fig:controlled-drainage}Controlled drainage system
located in the RD field with the collector drain coming from the field
going through the flowmeter, then the elbow on top of which a vertical
pipe section with holes to a defined height is placed to apply the
desired water level. Usually, this setup is placed in a control pit
within the field to not block the waterways.}
\end{figure*}

\begin{figure*}
\includegraphics{fig04}
\caption{\label{fig:evolution-selected}Three year time series showing:
(a) daily precipitation and potential soil moisture deficit (i.e.\ 
cumulated potential evapotranspiration--precipitation), (b) normalised
difference vegetation index (NDVI) obtained from remote sensing showing
the crops in CD \&amp; ND (dashed line) and RD (solid line) fields, (c)
water level imposed in the control pits, (d) cumulative yearly
discharged observed (reset to 0 on 1st March), (e) volumetric soil
moisture content at 0.3 m depth (SMC), (f) freshwater heads and (g)
electrical conductivity of the water inside the piezometers. These
time-series combined manual (dots) and sensor (line) data for one
location per field (CD2, RD2, ND2) as well as for the ditch close to
the RD outlet. Acquisition days of electrical resistivity tomography
(ERT) are denoted by stars in (f).}
\vspace*{2pt}
\end{figure*}


\subsection{Data processing}
EC and EC$_{\mathrm{a}}$ from ERT stick values presented in this work were
temperature corrected to 12~\textdegree C (average groundwater temperature of
the field) \mbox{following:} ${\mathrm{EC}}_{12} = \mathrm{EC}/(1+0.02\times (T-12))$
\citep{ma_comparing_2011} where $T$ is the temperature in degC.
Electrical resistivity data from surface arrays were processed using
ResIPy (v3.4.5, \citet{blanchy_resipy_2020, binley_1108_2015}).
Quadrupoles were kept if the current injected was larger than 1~mA,
stacking error smaller than 10\% and reciprocal error smaller than
20\%. The data were inverted on an axis-symmetrical mesh (resistivity
can vary with depth and away from the stick). The axis-symmetrical
constraint was imposed on a 3D mesh by defining rings of parameters,
similar to \citet{ronczka_monitoring_2020}. A difference inversion
(reg\_mode=2) scheme was used \citep{labrecque_difference_2001}. The
inversions converged in less than 5 iterations, reaching a final
weighted root mean squared close to 1. While the inversions were
successful, they tended to oversmooth the fresh--saline water boundary,
hindering the seasonal variations that could be observed in the raw
EC$_{\mathrm{a}}$. Hence, we decided to further present the resistivity data as
apparent electrical conductivity by selecting all quadrupoles where all
electrodes were spaced by two electrode spacing. The depth assigned to
the EC$_{\mathrm{a}}$ of a quadrupole is the midpoint of the quadrupole. The EMI data
processing included georeferencing and drift correction following
\citet{hanssens_robust_2020}. The obtained values are also displayed in
EC$_{\mathrm{a}}$ in mS/m. Statistical comparison between fields was done using
independent $t$-tests with scipy v1.14.5 \citep{virtanen_scipy_2020}. For
each $t$-test the values of three locations (at a given depth and time)
were compared between the field in controlled drainage (CD or RD) and
the reference field (ND). Significant differences were established when
the \mbox{$p$-value} was below 0.05.

\subsection{Management}
Two different drainage management methods were applied on the fields:
controlled drainage and regular drainage. In controlled drainage, the
groundwater table was managed by adjusting a pipe after the elbow
connected to the collector drain in the CD and RD field
(Figure~\ref{fig:controlled-drainage}). In regular drainage, the pipes
were open completely, allowing the free drainage. In 2022, all fields
were in regular drainage representing a reference situation (although
not all fields had the same crops). In 2023, CD field was in controlled
drainage (${+}$0.2~m from drain level at outlet or 0.7 m from the surface)
while RD and ND were in regular drainage. In 2024, CD and RD were in
controlled drainage (${+}$0.2~m from drain levels at outlet). The years
2023 and 2024 were wet and we did not raise the water level more than
0.2~m as the farmer did not want to risk part of the field to be
flooded, damaging crop growth. The water level in the field in
controlled drainage was occasionally lowered to drain level during
field operations (sowing and harvesting mainly).

\begin{figure*}
\includegraphics{fig05}
\vspace*{-3pt}
\caption{\label{fig:microtopo}(a) Microtopography of the fields around
the farm derived from the digital elevation model from Databank
Ondergrond Vlaanderen (DOV). (b) Electromagnetic induction map (EMI)
showing the apparent electrical conductivity for the HCP 1~m
configuration of the DUALEM-421S.}
\vspace*{-3pt}
\end{figure*}


\section{Results}
\subsection{Hydrology}

Figure~\ref{fig:evolution-selected} shows the evolution of the several
variables for selected locations (CD2, RD2, ND2). Data from all
locations are available in an interactive dashboard (see data
availability section). The year 2022 was driest, with a large PSMD peak
of 280~mm and was 2024 the wettest
(Figure~\ref{fig:evolution-selected}a). NDVI data shows the evolution
of the crops. In 2022 and 2023, different crops were grown in CD \&amp; ND
and RD fields (Figure~\ref{fig:evolution-selected}b), followed by grass
as cover crop in 2023 and 2024. The limited precipitation of 2022 and
the larger water uptake from the grass in RD explain the larger
decrease in groundwater observed for RD.
Figure~\ref{fig:evolution-selected}c shows the applied drainage depth
for each field. Figure~\ref{fig:evolution-selected}d shows the
cumulative discharge from the drains divided by the drained area of
each field. Note that the flowmeter in RD was only placed in autumn
2023. Drainage mostly occurs between September and January, but during
the summer there was also a drainage flux in the ND field in 2023. This
summer drainage is mostly due to intense summer precipitation events
and amounts to 33 (2023) and 44~mm (2024) per year. The soil moisture
(Figure~\ref{fig:evolution-selected}e) in the fields decreases during
summer months (up to 0.3 v/v) and recovers during winter (up to 0.4
v/v). Differences in soil moisture can be observed between the fields.
For instance in June 2023, CD and RD fields show larger moisture
content than the ND field. However, when all three locations of the
fields are considered, this difference is not significant. In May 2024,
the soil moisture content in the RD field was significantly larger than
the CD or ND fields. The freshwater heads followed the expected
pattern. They decreased during summer when there was insufficient
precipitation to recharge the aquifer and uptake from the growing
crops. During winter months there was a precipitation surplus that
recharges groundwater up to drainage level. The water table in the
field was often higher than the water table in the ditch but can also
go below (e.g.\ in 2022 in the RD field). Significant differences in
freshwater heads between the fields were observed in September 2022 (CD
higher than RD), June 2023 (CD and RD lower than ND) and November 2023
(RD lower than ND). The increment of 0.2~m in controlled drainage
fields was observed during winter months, but vanished after a month.
The summer decrease of the water table was accompanied by an increase
in the electrical conductivity of the water in the piezometer 
(ECpiezo)---here used as a proxy for salinity---. However, a lower water table
does not always involve a larger salinity. In 2022, for instance, the
water table drops much slower in CD2 than in RD2, but we recorded a
large increase in salinity in both wells.

\begin{figure*}
\includegraphics{fig06}
\vspace*{3pt}
\caption{\label{fig:evolution-rd}(a) Rainfall and potential soil
moisture deficit (PSMD ${=}$ cumulated potential
evapotranspiration---precipitation). (b) Freshwater head and (c)
electrical conductivity in the 3 m piezometer.}
\end{figure*}


\subsection{Spatial heterogeneity}
EMI mapping and the micro-topography map demonstrated the field
displays significant spatial heterogeneity. Figure~\ref{fig:microtopo}
shows the digital elevation model (DOV), revealing microtopographical
variations related to buried landforms and past land use.
Figure~\ref{fig:microtopo}b shows the map of the EMI on top of the
elevation model. Low-lying areas are generally associated with a higher
EC$_{\mathrm{a}}$. EMI data also reveal the presence of less conductive linear
features in the RD field, with RD3 being placed just in the middle of
one of these. These are likely related to past hydrological structures
(palaeochannels) that have been filled in with less conductive (sandy)
deposits. We hypothesize that this palaeochannel system continues in
the CD field at CD1, and then extends further north-west. Augerings
conducted during piezometer installation confirm that  RD3 and CD1 are
more sandy at depth.


Figure~\ref{fig:evolution-rd} shows the soil moisture content,
freshwater head and electrical conductivity of the groundwater for the
piezometer RD3 installed at 3 m depth in the RD field. This point is
located in the sandy channel detected by the EMI soil scan.  The
groundwater salinity in RD3 time series follows a different pattern
than the one in RD1 and RD2. While the \mbox{freshwater} head decreases for
all piezometers, the electrical conductivity of the groundwater in RD3
does not increase as in RD1 or RD2. The sandy channel probably stores
more fresh water since precipitation infiltrates more easily in that
soil texture and also lateral flow can occur. The effect of this
natural freshwater barrier formed by the sandy palaeochannel can be
well observed in the EMI map (Figure~\ref{fig:microtopo}). The part of
the field South of the channel shows a higher EC$_{\mathrm{a}}$ \mbox{compared} to the part
right above the channel. In the CD field, CD1 also shows a lower EC
compared to CD2 or CD3, possibly because it is also located in a
backfilled sandy channel.


One of the goals of controlled drainage is to store more freshwater
than in the case of regular drainage. Figure~\ref{fig:fluxes} proposes
an estimation of the repartition of the precipitation into different
fluxes. It shows that most of the drainage and the 
infiltration \unskip\break\mbox{occurs}
during winter months. Little drainage occurs during summer, mainly
during intense precipitation events. We previously showed that the
water from {intense} precipitation events is drained out of the field
into regular drainage (ND field), while controlled drainage (CD field)
retains this water so that it remains available to the crop later in
the season. This explains the difference in total drainage observed in
2023 and 2024 between CD and ND. 33 (2023) and 44~mm (2024) of water
was buffered in the controlled drainage field (CD). This amount, while
representing less than 10\% of the total water drained during a season,
is the equivalent of one irrigation  event.

\begin{figure*}
\vspace*{-2pt}
\includegraphics{fig07}
\vspace*{-4pt}
\caption{\label{fig:fluxes}Evolution of the amount of precipitation
distributed among drainage, infiltration and crop uptake flux. Crop
uptake is the potential evapotranspiration, and as such, is certainly
overestimated. Drainage flux is measured with the flowmeters.
Infiltration is what remains. When the total flux goes below the dashed
line (becomes negative), it means the precipitation is not sufficient
and groundwater is used to support crop growth. Numbers in parentheses
represent mm of precipitation.}
\vspace*{-3pt}
\end{figure*}

\subsection{Electrical resistivity}
Based on the monthly observed EC$_{\mathrm{a}}$ values along the sticks, the EC of
the water in the piezometer, and the lithology
(Figure~\ref{fig:lithology}), a threshold of 230 mS/m was estimated to
delimit the fresh--saline water boundary. This threshold is based on the
median between all times and locations of the middle of the range of
EC$_{\mathrm{a}}$ observed in the saturated zone. Data from CTD divers shows that the
EC of the water below this threshold is often larger than 10,000~$\upmu$S/cm
and up to 25,000~$\upmu$S/cm during summer peak
(Figures~\ref{fig:evolution-selected},~\ref{fig:evolution-rd}).
Figure~\ref{fig:lens} shows the evolution of this threshold in time. We
defined everything below the threshold as saline and everything above
it as fresh water. The top of the freshwater part represents the water
table. This figure depicts the evolution of the thickness of the
freshwater lens throughout three growing seasons. During summer, the
freshwater lens is increasingly exploited by the crop. In the summer of
2023 and in CD2, the freshwater lens was almost completely depleted.
During summer, the fresh--saline water boundary moves upward, possibly
due to the reduction of the vertical freshwater head.  Note that RD3
does not show EC$_{\mathrm{a}}$ values above 230 mS/m. It behaves differently, since
it is located in a sandy area within a palaeochannel (see
Figure~\ref{fig:microtopo}).

\begin{figure*}
\includegraphics{fig08}
\vspace*{-3pt}
\caption{\label{fig:lens}(a) Rainfall and potential soil moisture
deficit (PSMD ${=}$ cumulated potential
evapotranspiration--precipitation). (b--d) Estimations of the thickness
of the freshwater lens based on a 230 mS/m threshold applied on the
apparent electrical conductivity from the ERT sticks. The time
resolution of this figure was adapted to follow the resolution of the
ERT surveys that were carried out every month (precise dates in
Figure~\ref{fig:evolution-selected}c).}
\vspace*{-2pt}
\end{figure*}

To separate the static effect of the material electrical conductivity
from the dynamic effect of the pore water electrical conductivity,
time-lapse differences are shown in Figure~\ref{fig:diff-eca}.
Differences in EC$_{\mathrm{a}}$ are driven by soil moisture content above the water
table and by change in salinity below the water table. In the
unsaturated zone, soil moisture dynamics dominate the signal, although
simultaneously also changes in pore water concentration might be
occurring. There is an increase in EC$_{\mathrm{a}}$ below the water table in both
CD2 and RD1 during the summer of 2023, which aligns well with the trend
of the threshold shown above (Figure~\ref{fig:lens}). In contrast, the
decrease in soil moisture in RD1 during summer 2022 led to a decrease
in EC$_{\mathrm{a}}$. The dynamic of RD3 (piezometer located in the sandy channel) is
clearly different from CD2 or RD1 with lower magnitude of change and no
increase in EC$_{\mathrm{a}}$ below the water level during summer time. A slight
increase in EC$_{\mathrm{a}}$ above the water table can also be observed during
summer time in RD1, possibly explained by capillary rise of saline
water in the unsaturated zone. However, we acknowledge that more work
is needed to test this hypothesis.

\begin{figure*}
\includegraphics{fig09}
\caption{\label{fig:diff-eca}(a) Rainfall and potential soil moisture
deficit (PSMD $=$ cumulated potential
evapotranspiration---precipitation). (b) Difference in apparent
electrical conductivity for three locations with the water table in
cyan. Differences are computed compared to a ``wet reference'' survey
denoted by the vertical dashed green line. Increase in
EC$_{\mathrm{a}}$ can be associated with increase in saturation above
the water table and increase in salinity below the water table.}
\end{figure*}

\section{Discussion}
The effectiveness of controlled drainage depends on factors such as,
the distribution of the precipitation, as demonstrated by several
modelling studies \citep[e.g.][]{rodriguez_performance_2024}. Mainly in
years with summer droughts, agronomic benefits can be expected, since
controlled drainage assures more of the precipitation in spring and
summer is turned into soil water storage, instead of drainage. Among
the three monitoring years at our experimental site, only 2022 was a
``dry year''. However, in 2022, all three fields were still under
regular drainage. Different crops were grown in the RD (grass) and CD
(flax) field, which had a large effect on the groundwater table
(Figure~\ref{fig:evolution-selected}). In the years 2023 and 2024,
controlled drainage was implemented, but those years were very wet.
This abundance of summer precipitation resulted in a lack of
significant differences in yield between the controlled drainage fields
and the regular drainage, since no drought stress was occurring in
either of them. Nonetheless, \citet{youssef_impact_2023} also found
little to no increase in corn yield with controlled drainage based on
the 55 site-years data from several fields in the US. Similarly, a
world-wide meta-analysis of \citet{wang_effects_2020} found that
controlled drainage increases yield by 0.11\% on average. \mbox{Controlled}
drainage also has the potential to increase the retention time of
nutrients and fertilizer in the field. While investigating this was
beyond the scope of this work, this could equally impact crop health
\citep{castellano_sustainable_2019}.

While we saw a pronounced seasonal effect on the fresh--saline water
interface, we could not see a clear difference between controlled and
regular drainage. We expected that the combined low water level in the
ditch surrounding the field (due to the polder water board) and the
higher head in the field (due to controlled drainage) would have
encouraged saline water to flow from the field to the ditch. However,
this process can be slow and longer term studies will be needed to
observe this effect.

From piezometer data, saline water can be found at various depths
within the same field. The reason for the differing data in several
piezometers in the same field became clearer with the help of
geophysics (EMI map in Figure~\ref{fig:microtopo}). Similarly, while
the EC of the water in the piezometer provides a good proxy for the
depth of the saline water, the addition of the ERT sticks to locate the
fresh--saline water boundary in the bulk soil (Figure~\ref{fig:lens}) is
unique. Overall, the heterogeneity of the agricultural field,
especially the presence of the sandy channel and the presence of peat
layers with higher hydraulic conductivity than the clay layers may have
a large effect on the field hydrology, maybe even larger than the
effect of controlled drainage. Such structures are not uncommon in
polder areas, whether their origin is natural or artificial (deviation
of water course or merging of agricultural parcels).

The 230 mS/m threshold is a relatively simple approach to delineate the
fresh-saltwater interface, but we also observed that the higher EC$_{\mathrm{a}}$
values were co-located with the presence of peat
(Figure~\ref{fig:lithology}). Hence, one can wonder how to distinguish
the static \mbox{contribution} of the soil materials from the contribution of
the pore water EC. Petrophysical models (e.g.\ 
\xcitealp{archie_electrical_1942}{1942} or 
\xcitealp{waxman_electrical_1968}{1968}) could
be applied per material. However, given the different support volumes
of the ERT sticks and the piezometer, we choose to not explore a more
advanced approach in this manuscript. Instead, we separate the static
effect of the material electrical conductivity from the dynamic effect
of the pore water electrical conductivity by looking at time-lapse
differences (Figure~\ref{fig:diff-eca}).

Typically resistivity readings obtained from ERT sticks are inverted to
estimate the exact depth of the fresh--saline interface 
\citep[e.g.][]{ronczka_monitoring_2020}. For this work, we choose not to
present the inverted results, but to work with the raw temperature
corrected EC$_{\mathrm{a}}$ instead. While the axis-symmetrical inversions of the ERT
sticks converged well and provided meaningful depth-specific insights
into the lithology, the evolution of the fresh--saline boundary
established based on the 230 mS/m threshold was lost during the
smoothness-constrained inversion. This can be partly explained by the
imposed constraints. We hypothesize that, during the summer, the
greater extent of the unsaturated zone (more resistive) and the
increase in salinity in the deeper layer (less resistive), can
compensate and be smoothed out during the inversion process. The
inclusion of the measured water table as a sharp boundary could
potentially help to solve the issue even if the capillary zone in clay
soil is likely a smooth transition between saturated and unsaturated
zone. The effect of the unsaturated zone on the inversion was already
mentioned by \citet{velstra_observations_2011}. Our higher
time-resolution 1D data make them more sensitive to this effect.
However, in our setup, the measurement of vertical quadrupoles along
the ERT sticks enables us to locate the depth of the fresh--saline water
interface accurately compared to a setup with only surface electrodes.

\section{Conclusion}
The effect of controlled drainage on the seasonal dynamics was minimal
in our study, probably due to the wet conditions in comparing
controlled and regular drainage. Controlled drainage was still able to
buffer intense precipitation events (up to 44~mm in 2024) which could
have been beneficial to crops should a long dry period have occurred
subsequently. The geophysical measurements (EMI and ERT) proved useful
in unravelling the field-scale spatial heterogeneity and helped in the
interpretation of traditional hydrological point sensors. Field
heterogeneity, including human-induced and natural structures, play an
important role in the hydrological functioning of the studied parcels.
This is a situation which is likely to occur in many polder landscapes
and was revealed thanks to EMI measurements. The evolution of the raw
EC$_{\mathrm{a}}$ values from the ERT sticks enable us to follow the freshwater lens
thickness and observe how, as the freshwater lens decreases during
summer, the saline groundwater tends to rise up. However, no
significant effect of controlled drainage on the evolution of the
fresh--saline water interface was observed. While, additional
information from piezometers and augering is needed to correctly
interpret the geophysical data, the ERT and EMI techniques offer
invaluable spatial and temporal information at relevant scales to the
study of the fresh--saline water interface for agronomical applications.

\section*{Data and code availability}
All the data and code used in this study is available at
\url{https://github.com/op-peil/paper-setup} \citep{Blanchyetal2025}.

\section*{Declaration of interests}
The authors do not work for, advise, own shares in, or receive funds
from any organization that could benefit from this article, and have
declared no affiliations other than their research organizations.

\section*{Authorship statement (CreDIT)}
Conceptualization: GB, SG, TH, FN, PS, DH; formal analysis: GB, ER;
data curation: GB, ER, BE, AM, DC, PS; writing - original draft: GB;
writing - review and editing: All authors; project administration: GB,
SG, TH, FN, PS, DH.

\section*{Funding}
GB is a Research Fellow of the Fonds de la Recherche
Scientifique---FNRS (CR: 1.B.044.22F). The experimental site and the
majority of the hydrological data were collected in close collaboration
with the OP-PEIL project (VLAIO HBC.2020.3159) funded by the Flemish
Government.

\section*{Acknowledgments}
We would like to thank Valentijn Van Parijs for doing most of the EMI
data collection and Dirk Demeyere for letting us run this experiment in
his fields.

\CDRGrant[FNRS]{1.B.044.22F}
\CDRGrant[VLAIO]{HBC.2020.3159}

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