Karst water resources play an important role in drinking water supply but are
highly vulnerable to even slight changes in climate. Thus, solid and
spatially dense geological information is needed to model the response of
karst hydrological systems to such changes. Additionally, environmental
information archived in lake sediments can be used to understand past climate
effects on karst water systems. In the present study, we carry out a
multi-methodological geophysical survey to investigate the geological
situation and sedimentary infill of two karst lakes (Metzabok and Tzibaná)
of the Lacandon Forest in Chiapas, southern Mexico. Both lakes present large
seasonal lake-level fluctuations and experienced an unusually sudden and
strong lake-level decline in the first half of 2019, leaving Lake Metzabok
(maximum depth ∼25m) completely dry and Lake Tzibaná (depth
∼70m) with a water level decreased by
approx. 15 m. Before this event, during a lake-level high stand in
March 2018, we collected water-borne seismic data with a sub-bottom profiler
(SBP) and transient electromagnetic (TEM) data with a newly developed floating
single-loop configuration. In October 2019, after the sudden drainage event,
we took advantage of this unique situation and carried out complementary
measurements directly on the exposed lake floor of Lakes Metzabok and
Tzibaná. During this second campaign, we collected time-domain induced
polarization (TDIP) and seismic refraction tomography (SRT) data. By
integrating the multi-methodological data set, we (1) identify 5–6 m
thick, likely undisturbed sediment sequences on the bottom of both lakes,
which are suitable for future paleoenvironmental drilling campaigns, (2)
develop a comprehensive geological model implying a strong interconnectivity
between surface water and karst aquifer, and (3) evaluate the potential of the
applied geophysical approach for the reconnaissance of the geological
situation of karst lakes. This methodological evaluation reveals that under
the given circumstances, (i) SBP and TDIP phase images consistently resolve
the thickness of the fine-grained lacustrine sediments covering the lake
floor, (ii) TEM and TDIP resistivity images consistently detect the upper
limit of the limestone bedrock and the geometry of fluvial deposits of a river
delta, and (iii) TDIP and SRT images suggest the existence of a layer that
separates the lacustrine sediments from the limestone bedrock and consists of
collapse debris mixed with lacustrine sediments. Our results show that the
combination of seismic methods, which are most widely used for lake-bottom
reconnaissance, with resistivity-based methods such as TEM and TDIP can
significantly improve the interpretation by resolving geological units or
bedrock heterogeneities, which are not visible from seismic data. Only the use
of complementary methods provides sufficient information to develop
comprehensive geological models of such complex karst environments
Introduction
About 7 %–12 % of the world's continental area is covered by karst
(e.g., Hartmann et al., 2014) and up to one-quarter of the earth's population
at least partially depends on drinking water from karst systems (e.g., Ford
and Williams, 2007). Even though continued population growth and
industrialization put pressure on these important resources in terms of both
water quantity and quality, the response of karst systems to expected future
climate change is still not well understood (Hartmann et al., 2014).
Groundwater models offer one opportunity to estimate future changes in water
availability but heavily depend on reliable and spatially dense geological
information. Where direct geological information, e.g., from drillings, is not
dense enough or not available at all, geophysical methods can be used to
provide quasi-continuous indirect information on the subsurface geology in
karst areas (Bechtel et al., 2007).
Another possibility to understand climatic effects on karst water systems
relies on the analysis of paleoenvironmental records (e.g., Medina-Elizalde
and Rohling, 2012; Vázquez-Molina et al., 2016). In particular, lake
sediments are important archives of freshwater and terrestrial environmental
information, and sediment cores can be used to reconstruct past climate and
ecological changes in the lakes (Cohen, 2003; Schindler, 2009; Pérez
et al., 2020). Thus, paleoenvironmental studies give insight into the local
links between climate variations and the availability (and quality) of water in lakes
and the connected karst aquifer system. To identify suitable drilling
locations providing continuous paleoenvironmental records at a high temporal
resolution, knowledge about sediment thickness and composition, depth to
bedrock, and possible heterogeneities within the lake sediments is needed
(Last and Smol, 2002).
Geophysical methods can efficiently provide such information from the local
scale up to the lake-basin scale and can (principally) be employed on both
land and water. Due to the usually sharp contrast between seismic velocities
of sediment layers and the underlying bedrock, (reflection-)seismic methods
are often given priority over other geophysical methods for lake-bottom
reconnaissance (Scholz, 2002). In particular, low-frequency echo sounders
(e.g., Dondurur, 2018), also referred to as sub-bottom profilers (SBPs), allow sediment deposits of several tens of meters to be quickly mapped based on
single-channel seismic data. Nevertheless, electrical-resistivity images
provided by electrical resistivity tomography (e.g., Binley and Kemna, 2005)
or electromagnetic soundings (e.g., Kaufman et al., 2014) complement the
mostly geometrical information obtained from reflection-seismic or sub-bottom
profiling measurements (Butler, 2009). Under certain conditions such as high
lake-bed reflectivity and/or low reflectivity of targeted boundaries, seismic
methods may, however, provide insufficient results, and therefore alternative
methods are needed.
Recent studies using direct-current (DC) electrical resistivity for
water-borne investigations on freshwater bodies include surveys with floating
(e.g., Befus et al., 2012; Orlando, 2013; Colombero et al., 2014) or
underwater electrode chains (e.g., Toran et al., 2015) and provide evidence
for the potential of this method for shallow-water applications. Electrical
resistivity can also be assessed by electromagnetic methods, which, compared
to DC resistivity measurements, offer a more compact experimental
layout. Electromagnetic surveys are often carried out as transient
electromagnetic (TEM) soundings with floating magnetic sources and
receivers. Hatch et al. (2010), for example, used an in-loop configuration
with a ∼7.5m×7.5m transmitter and a ∼2.5m×2.5m receiver to map river bed salinization in
an Australian river with an average water depth of 5–10 m. Mollidor
et al. (2013) used a similar but slightly larger setup (∼18m×18m transmitter, ∼6m×6m
receiver) to map a thick conductive sediment layer below the bottom of a
20 m deep maar lake in Germany. More recently, Yogeshwar et al. (2020)
used the system developed by Mollidor et al. to image a volcanic lake
hydrothermal system on the Azores, whereas Lane et al. (2020) introduced a
compact floating TEM system, designed for the rapid electrical mapping of the
subsurface of rivers and estuaries. Some older relevant case studies with
shallow-water applications of both techniques, DC resistivity and
electromagnetic soundings, were reviewed by Butler (2009).
In a previous study, we successfully used geoelectrical and electromagnetic
methods to investigate the sedimentary infill of two desiccated lakes in a
volcanic area (Bücker et al., 2017; Lozano-García et al., 2017). To
extend our investigations, in this study, we evaluate the potential of land
and water-borne resistivity-imaging methods to complement seismic methods for
the investigation of karst lakes in the Lacandon Forest, southern
Mexico. Recent biological and abiotic studies have highlighted the great
potential of sedimentary sequences from the lakes of this remote area as
continuous paleoenvironmental and paleoclimatic records during the late
Quaternary (e.g., Díaz et al., 2017; Echeverría-Galindo et al.,
2019; Charqueño-Celis et al., 2020). In this study, we focus on Lakes
Metzabok and Tzibaná, two of the largest lakes of the Lacandon Forest,
which experienced a sudden and catastrophic lake-level drop in the first half
of 2019. While large seasonal lake-level variations are part of the nature of
both lakes, it remains unclear whether such particular events as the one
observed in 2019, which left Lake Metzabok completely dry, are also recurrent
with a frequency of several decades or rather linked to recent climate
change. To better understand possible draining mechanisms and their triggers,
besides further paleoenvironmental investigations, a comprehensive geological
picture of the lakes' geological situation is essential.
In 2018, roughly one year before the drainage event and when the lakes were
filled, we collected seismic data with a SBP and carried out TEM soundings to
assess the electrical resistivity of the lake bottom and obtain information on
the thickness of the sedimentary infill. The sudden drainage of the
investigated lakes in 2019 provided us with the unique opportunity to collect
additional data directly on the dry lake bed. Seismic data were then
recollected with a seismic refraction tomographic (SRT) setup in order to
provide information on both refractor geometry and seismic velocities of the
different geophysical units. Additional electrical imaging data were measured
with the time-domain induced polarization (TDIP) method, which has fewer
limitations regarding the detectability of thin near-surface layers and
heterogeneities than the transient electromagnetic method. Furthermore, the
polarization properties of the subsurface materials assessed by TDIP
measurements provide additional information and can improve the interpretation
of TEM and TDIP resistivity results.
Based on the above considerations, our study has three main objectives: (1)
identify suitable drilling locations to obtain undisturbed and far-reaching
sedimentary sequences for paleoenvironmental reconstructions, (2) provide basic
knowledge on the geological situation of the studied lakes (sediment cover,
limestone bedrock and possible connectivity with the karst aquifer), and (3)
develop and apply a multi-methodological geophysical approach with a special
focus on the evaluation of the potential of water-borne TEM soundings for
lake-bottom reconnaissance.
Study area
The study area is located in the Lacandon Forest (16–17.5∘ N,
90.5–92∘ W; 500–1500 ma.s.l.), which occupies the
northeastern part of the state of Chiapas, Mexico (Fig. 1a). The region
belongs to the Chiapas fold belt with its WNW-trending folds and thrusts,
which mainly developed in massive Cretaceous limestone (García-Gil and
Lugo Hupb, 1992). The orogeny of the Chiapas fold belt is related to the
collision of the Tehuantepec Transform/Ridge on the Cocos plate with the
Middle America Trench during the Middle Miocene (Mandujano-Velazquez and
Keppie, 2009). The resulting anticlines and synclines dominate the topography
in the study area forming long WNW-directed valleys and mountain ranges. The
tectonically fractured limestone geology, in conjunction with the humid
subtropical climate, favor an intensive karstification (García-Gil and
Lugo Hupb, 1992). In the valleys, lakes formed by bedrock dissolution, such as
dolines (or sinkholes), uvalas (formed by two or more dolines) and poljes
(larger karst depressions), are mostly aligned in the main fold direction.
Layout of the geophysical survey on lakes Metzabok (a) and
Tzibaná (b) in October 2019 (after the sudden lake-level drop) including
sub-bottom profiler (SBP), transient electromagnetic (TEM), time-domain
induced polarization (TDIP), and seismic refraction tomography (SRT)
measurements. The geophysical measurements discussed here are grouped into
six profiles; black triangles next to the profile names indicate the
profile orientations. Yellow and blue triangles indicate sampling locations
for sediment and water samples analyzed in the laboratory, respectively. The
dashed black line in (b) indicates the dry part of the river delta exposed
during October 2019.
The lake system of Metzabok (17∘6′30′′–17∘8′30′′ N,
91∘36′30′′–91∘38′50′′ W, ∼550ma.s.l.) consists of 21 lakes of different sizes, the majority
of which are interconnected when water levels are high (Lozada Toledo,
2013). The two largest lakes of the system are Lake Tzibaná (area
1.24 km2; max. depth 70 m) and Lake Metzabok
(0.83 km2; 25 m) (see Fig. 1b). The river Nahá is the
principal superficial tributary connecting the lake system of Metzabok with
the one of Nahá (∼830ma.s.l.); a superficial outlet of
the lake system does not exist. Although the (additional) water supply and
discharge through the underlying karst system is unknown, fast lake-level
changes indicate substantial groundwater–surface-water connections. Usually,
seasonal lake-level changes amount to ∼10m and can be traced
back to pre-Hispanic times (Lozada Toledo, 2013). Between March and August 2019
an extreme lake-level drop occurred that left Lake Metzabok completely dry and
decreased the water level of Lake Tzibaná by ∼15m.
Data acquisition and processing
With the primary goal of mapping sediment thicknesses below the lake floor of
various lakes of the karst lake systems of Metzabok and Nahá, we carried
out a first geophysical campaign employing seismic (SBP) and TEM methods, when
lake levels were maximum in March 2018 (Fig. 2a). Immediately after the dramatic
lake-level decline, we revisited the study site in October 2019 to collect
SRT data and perform TDIP measurements
directly on the dry lake bottom (Fig. 2a and b).
Electrical resistivity measurements in the laboratory
In October 2019, a total of six surface sediment samples (top 10 cm)
and two water samples were collected at different locations for laboratory
analyses (see sampling locations in Fig. 2a and b). On the dry lake bottom,
sediment samples were collected using a small spade, whereas an Ekman grab
sampler was used to retrieve sediment samples from water-covered
areas. Sediment samples were stored in sealed plastic bags in order to prevent
the loss of moisture; water samples were stored in plastic bottles. All
samples were kept cool during transport and storage in order to prevent an
increased degradation of organic matter. The electrical conductivity of the
water samples (at 20 ∘C) was measured with a laboratory
probe. The frequency-dependent complex electrical resistivity of the samples
was measured using a Chameleon I measuring device (Przyklenk et al., 2016) in
the frequency range from 1 mHz to 240 kHz. To this end, the
unconsolidated sediments were filled into four-point measuring cells with
non-polarizing potential electrodes as used by Kruschwitz (2007) and Bairlein
et al. (2014). Prior to and during the measurement, the measuring cell was
stored in a climate chamber to keep the sample at a constant temperature of
20 ∘C. Measurements were repeated over a period of 4 to
5 d after filling the cell and inserting it into the climate chamber
in order to assure equilibrium conditions in the sample. Measurements on
relatively dry samples (MET19-A and TZI19-A) resulted in comparably high phase
values. These samples were removed from the measuring cell, saturated with
water of the corresponding lake (using one of the two water samples), and
filled again into the measuring cell. This procedure led to more consistent
phase measurements compared to the other samples.
Collection of sub-bottom profiler (SBP) lines
Low-frequency echo-sounders, often referred to as sub-bottom profilers,
are single-channel seismic reflection systems, which are used to obtain
bathymetric profiles and provide a high-resolution stratigraphic display of
the uppermost sediments (e.g., Dondurur, 2018). In March 2018, SBP lines were
collected with the 10 kHz transducer StrataBox HD (SyQwest), which has
an output power of 300 W, mounted on a motor boat. Data were recorded
with a record length of 200 ms and a 1024 Hz sampling
frequency. The SBP device was mounted mid-ship in a side mount
configuration, with the transducer positioned at 0.4 m below the water
surface. Prior to each survey, the acoustic wave velocity profiles of the
water columns of the two studied lakes were measured with a Digibar S (Odom
Hydrographic). SBP lines were laid out in a regular NS- and EW-oriented grid
with separations of 100 and 300 m, respectively (see
Fig. 1b). Navigation data were measured with a differential GPS and stored
along with the SBP data.
During processing, the SBP acoustic traces were read in using code provided by
Kozola (2011) and visualized using a MATLAB script available with this
paper. The average value of the acoustic wave velocity of the water
column (1486.6 ms-1 for both lakes) was used to convert the two-way travel time of
the acoustic pulse into a depth scale for the seismic profiles.
Transient electromagnetic (TEM) soundings
TEM soundings were carried out from the water
surface using a single-loop configuration in March 2018. The loop with a
diameter of 22.9 m (surface area: ∼412m2) consisted of
a single, insulated copper wire attached to a floating ring made of 24 PVC tubes (diameter 1 in). The ring was towed by an inflatable boat
equipped with an electric motor, which was only turned on for navigation
between sounding sites. During the measurements, the loop was separated by
5 m from the inflatable boat. Depending on the specific wind
conditions, the unanchored system slowly drifted during the measurements
resulting in maximum displacements of approximately 2 times the loop
diameter (i.e., ∼40m). Due to the comparably low measurement
velocity (ca. 3 min per sounding) and the poor maneuverability of the
experimental setup, TEM data were acquired along a limited number of
irregularly distributed lines of interest (Fig. 2a).
A simple echo-sounder (Garmin Fishfinder series) was used to measure the water
depth at each sounding site. A TEM-FAST48 (manufactured by Applied
Electromagnetic Research) was used for the acquisition of TEM sounding data.
Transients were recorded using a transmitter current of 1 A and 32
time gates between 3.6 and 1024 µs after current shut-off. For this
transient length, the measuring device records 64 transients, which are
analogously averaged by the hardware. For one sounding measurement, this basic
measuring cycle is repeated n×13 times. For n=4, which we used for
our measurements, this results in 52 repetitions of the basic cycle and a
total of 3328 effective stacks, which are used to compute the impulse response
by digital averaging and to determine the measurement error as the standard
error of the mean (SEM). For times around 200 µs (the latest time
gates used for the inversion), the SEM is 5×10-9VAm-2. For exemplary TEM data and errors, see Fig. A1
of the Appendix.
During the processing, all transients were truncated to times from 21.4 and
174.5 µs and inverted using the software ZondTEM1d (Alex Kaminsky,
personal communication, 2020). A
conventional 1D smoothness-constrained modeling approach was used to obtain a
one-dimensional multilayer model (20 layers) for each sounding position
separately. ZondTEM1d supports arbitrarily shaped loops, whose vertices can be
defined independently for transmitter and receiver to ensure the correct
interpretation of the coincident-loop data. The same software was also used
to adjust layered models (five layers). In both cases (smooth and layered model),
the water depth measured with the echo-sounder was used as a priori
information by fixing the thickness of the first layer to this value. The
electrical resistivity of the water layer was fixed to 25 Ωm. This
value was manually adjusted to provide a good overall fit for all
soundings. Especially for sites with shallow-water depths and a resistive lake
bed (i.e., bedrock not covered by conductive sediments), constraining the
resistivity of the water layer significantly improved the imaging
results. Multidimensional effects, as investigated in detail by Mollidor
et al. (2013) for TEM data from a lake with steep bathymetric slopes, were not
considered in the interpretation as the bathymetric variation along our survey
lines was relatively gentle. Following the approach by Yogeshwar
et al. (2020), which is based on the one by Spies (1989), we estimate the
depth of investigation of our TEM soundings based on transmitter area
and current, average subsurface resistivity (of the smooth models), and
late-time induced voltage.
Time-domain induced polarization (TDIP)
Time-domain induced polarization (TDIP) data were acquired with a SyscalPro
Switch 48 device (IRIS Instruments) using 48 stainless-steel electrodes
separated by 5 or 10 m depending on the target. The soft and wet mud
on the exposed lake bed provided a good contact between the electrodes and the ground.
Where TDIP profiles crossed limestone outcrops, electrodes were inserted into
sediment-filled fractures in order to keep contact resistances as low as
possible. Measurements were carried out with injection currents between 0.5
and 1 A, one single stack and a 50 % duty cycle with
500 ms pulse length (i.e., duration of off time is also
500 ms). After an initial delay of 20 ms after current shut-off, the voltage decay was sampled in 20 time windows with a constant length
of 20 ms. We used a dipole–dipole configuration combining short dipole
lengths of one electrode spacing for superficial measurements with longer
dipole lengths of 2 and 4 times the electrode spacing for moderate and
large depths, respectively. To prevent loss of data quality due to remnant
electrode polarization (e.g., Dahlin et al., 2002), the measurement protocol
avoids potential readings using electrodes that had been used as current
electrodes before (Flores Orozco et al., 2012, 2018a). TDIP lines of varying
length were laid out along (and parallel to) selected 2018 SBP and TEM lines
on both lakes (Fig. 2a and b). In order to cover the full length of the
north–south-running SBP line L4 NS, TDIP lines MET19-1 and MET19-2 were
carried out as a roll-along profile with an electrode spacing of 10 m
and an overlap of 12 electrodes.
During the processing, we removed erroneous measurements defined as those
associated with negative apparent resistivity and/or integral chargeability
readings (Flores Orozco et al., 2018b). After the removal of erroneous
measurements, raw-data pseudo-sections were inspected and additional outliers
were defined as those readings with integral chargeability values above
8 mVV-1. Based on an exemplary data set, this processing approach
is further discussed the Appendix. Integral chargeability values were then
linearly converted to frequency-domain phase shifts assuming a constant phase
angle response (i.e., no frequency dependence) following the approach outlined
by Van Voorhis et al. (1973) and implemented by Kemna et al. (1999). Finally,
2D complex-resistivity sections were reconstructed from the filtered data
using the smoothness-constrained least-squares algorithm CRTomo (Kemna,
2000). 2D sections are only visualized down to an estimated depth of
investigation by blanking model cells with cumulated sensitivity values 2 orders of magnitude smaller than the maximum cumulated sensitivity (i.e., the
sum of absolute, data-error weighted sensitivities of all considered
measurements; e.g., Weigand et al., 2017).
Seismic refraction tomography (SRT)
SRT data were acquired with the 24-channel
seismograph Geode (Geometrics) and 24 28 Hz geophones
installed along a line at 5 m spacing in October 2019. To generate the
seismic signal, a 7.5 kg sledgehammer hitting a steel plate was used
at 25 shot points between the geophone positions as well as at distances of
2.5 m from the first and last geophone, respectively. At each shot
point, five shots were stacked to improve the signal-to-noise ratio. Due to
the limited length (115 m between the first and the last geophone) and
investigation depth, SRT data were only collected in the central parts of
selected TDIP profiles (Fig. 2a and b).
During the processing, we applied a 120 Hz low-pass filter on the
seismic traces to remove high-frequency noise and allow for a more accurate
picking of first break travel times. A tomographic inversion scheme then
determines the two-dimensional velocity structure below the SRT profile based
on the first-arrival travel times (e.g., White, 1989). For the filtering of
the seismic traces and picking of the first arrivals, we used a Python toolbox
developed at the TU Wien. The observed travel times were inverted with the
pyGIMLi framework (Rücker et al., 2017) following a smoothness-constrained
scheme. Based on the ray paths computed for the resolved velocity model (e.g.,
Ronczka et al., 2017), we also determine the so-called ray coverage, which
permits the depth of investigation to be illustrated by blanking models cells that
are not covered by any ray.
Results and interpretationLaboratory measurements – electrical properties of sediment and water
samples
The complex-resistivity measurements on the six sediment samples carried out
in the laboratory (Fig. 3a) show that most resistivity values vary within a
relatively narrow range between 10 and 15 Ωm. Only the
resistivity of one sample (TZI19-A) from the river delta in Lake Tzibaná
reached values between 18 and 20 Ωm. Figure 3b shows that phase
values (here -φ) in the frequency range from 1 to 10 Hz,
which is mainly tested by our TDIP measurements, roughly range between
0.5 and 4 mrad. Again, the only exception is sample TZI19-A with
phase values of up to 6 mrad in the relevant frequency range. We
attribute the atypical behavior of the sample TZI19-A to its fluvial nature
(coarse grains and high organic content), while the remaining samples are
clearly lacustrine (fine grains and lower organic content). The elevated phase
values at high (>1kHz) frequencies, which can be observed for all
six samples, are typical electromagnetic coupling effects (Pelton et al.,
1978) but do not affect our TDIP measurements, due to the long initial delay
before the sampling of the voltage decay starts.
Frequency-dependent complex resistivity of six lake-bottom
sediment samples retrieved from Lake Metzabok (triangles) and Lake
Tzibaná (crosses). Complex-resistivity values are given in terms of (a)
magnitude and (b) phase. The highlighted frequencies between 1 and 10 Hz
roughly correspond to the range tested by our time-domain induced
polarization measurements in the field.
The resistivity of the two water samples from the remaining water bodies used
to improve the readings of two dry samples (MET19-A and TZI19-A) were
11.9 Ωm (Metzabok) and 26.8 Ωm (Tzibaná),
respectively. They are significantly lower than the average water resistivity
of ∼34.5Ωm reported by Rubio Sandoval (2019) for water
samples collected from Lake Metzabok during high lake-level stands in 2016.
This reduction of electrical resistivity (i.e., increase in conductivity) is
probably due to the larger effect of evaporation on the salinity of small (and
shallow) water bodies. Indeed, the remaining water body in Lake Metzabok was
much smaller (∼50m2) than the one in Lake Tzibaná (∼5000m2). However, a comprehensive understanding of the strong
variation of water conductivity with respect to both sampling location and
time is the subject of ongoing limnological research in the study area.
The average resistivity of the sediment samples for the frequency range
between 1 and 117 Hz (and excluding sample TZI19-A) is
12.25 Ωm, which is typical for saturated clayey sediments (e.g.,
Reynolds, 2011). Note that due to the contribution of surface conduction along
the charged clay-mineral surfaces (Waxman and Smits, 1968), the bulk
resistivity of the sediments is even lower than the average resistivity of the
water (25–35 Ωm during high lake-level stands). In our case,
this resistivity contrast between lake water and sediments by a factor of 2 to
3 is of particular relevance as it allows us, in principle, to detect the two
materials as separate units. To our best knowledge, this is the first time
that the phase spectra of fresh lake-bed sediments have been measured in the
laboratory.
Field measurements on Lake Metzabok
In October 2019, Lake Metzabok (average depth 15 m) was completely
dry, except for some residual ponds. Its sediment-covered bottom is mostly
flat with steep walls (>50% slope) and some cliffs along the
shore line (Fig. 4a). Only some drainage channels, steep limestone hillocks,
and small ponds (Fig. 4a–d) eventually disrupt the smooth lake-bottom
topography.
Profile 1 – SBP and TDIP results reveal three distinct geological
units
The north–south-oriented SBP line on Profile 1 crosses a number of these
limestone hollocks and depressions, which are well resolved by the first
reflector in the seismogram (Fig. 4e). Within the depressions between the
limestone outcrops, a second reflector can be resolved, the geometry of which
shows a certain consistency with the surface of the limestone outcrops. This
reflector can be interpreted as the lower limit of the sediment cover. The SBP
data show that not only the elevations (outcrops) but also the depressions in
the sediment cover are influenced by the topography of the underlying
limestone: both depressions, the drainage channel in the northern as well as
the small pond in the southern part, are associated with local risings of the
limestone surface. Based on the SBP images, the sediment thickness mostly
varies between 5 and 7 m along Profile 1.
Topographic features and geophysical sections along Profile 1 of
Lake Metzabok. Photographs taken in October 2019: (a) lake basin with flat
bottom, (b) drainage channel, (c) limestone hillock, (d) deep fracture and
pond next to shallow limestone outcrop. (e) Sub-bottom profiler (SBP)
section with dashed lines highlighting the main reflector encountered below
the lake floor and dotted lines outlining a zone of high diffuse
reflectivity.(f, g) Electrical resistivity and phase images,
respectively, including electrode positions (black dots along the surface)
and dotted lines taken from SBP section. Electrical sections are shifted by
25 m with respect to the SPB section. Labels in the lower-left corners of
(f and g) represent the amount of data points used for the inversion
compared to the total measured data (same for resistivity and phase) and the
respective percentage root mean square (RMS) deviations of the inversion.
Below the surface of the limestone outcrops and the lower limit of the
sediment cover, respectively, we observe zones of diffuse reflectivity. These
might be related to the heavily fractured and dissolved limestone.
Particularly in the flat areas, the sediment cover might also be underlain by
blocks of collapsed limestone with sediment filling the spaces between blocks
and debris. The lakes of the study area show all characteristics of karst
lakes, which are expected to originate from collapsed karst cavities, and the
collapse debris should still be present below the sediment cover.
The electrical images obtained from the co-located TDIP line support this interpretation. The resistivity image (Fig. 4f) shows a gross
separation into two main units: the (i) sediments as well as the supposed
limestone debris–sediment mixture stand out with low resistivity values
between 10 and 20 Ωm, while the (ii) limestone outcrops and the
deep part of the section are characterized by higher resistivity values of up
to 300 Ωm. The phase image (Fig. 4g) also shows a separation
into units with low and intermediate phase values. Here, a much thinner top
layer (compared to the conducting layer in Fig. 4f) stands out with phase
values between 0 and 5 mrad, while the limestone bedrock shows phase
values >5mrad. The capability to separate the pure sediments from
the limestone–sediment mixture underlines the benefit of evaluating the TDIP
phase. Due to the relatively low data cover after outlier removal for large
dipole separations, we do not interpret the phase values at depths >50m.
For the sediment infill, both the resistivity values of 10–20 Ωm and the phase values below 5 mrad are in agreement with our
laboratory measurements on the sediment samples of Lake Metzabok,
corresponding to an average resistivity of ∼12Ωm and
phase values (here -φ) <4mrad. In contrast, resistivity
and phase values associated with the limestone bedrock are significantly
higher than those of the fine-grained sediment cover. The intermediate layer,
which we interpret as mixture of fine-grained sediments and the collapse
debris, seems to inherit the low resistivity of the supposed clay-rich matrix,
while the phase or polarization response is increased by the limestone debris.
Profile 2 – SRT measurements confirm the presence of three geological
units identified in the TDIP images
The north–south-oriented Profile 2 runs parallel to the last part of Profile 1
but is shifted ∼10m east. It is centered at the small pond
(Fig. 4d) and has a smaller electrode spacing (5 m instead of
10 m) to better resolve the sediment-limestone contact below the
bottom of the pond. The electrical images (Fig. 5a and b) show the same
characteristics as seen in the corresponding part of Profile 1. Due to the
higher resolution, here, we observe an internal layering of the shallow
conductive units with a less conductive (30–50 Ωm) top layer of
∼10m thickness and a more conductive (<20Ωm)
layer that extends down to 30 m in the northern and southern parts of
the line. The separation into two units becomes more obvious in the phase
image, where the superficial layer is less polarizable (well below
4 mrad) than the deeper part. A few meters east of the center of the
profile, the resistive limestone bedrock crops out, which might explain the
significantly increased resistivity (>100Ωm) and phase
values (>6mrad) over the first 20 m of depth below this
part of the profile.
Geophysical sections along Profile 2 of Lake Metzabok (same
coordinates as in Fig. 4): (a and b) electrical resistivity and phase
images, respectively, including electrode positions (black dots along the
surface), sampling locations of sediment samples (red diamonds at the
surface), and the main lithological units interpreted from the SBP image
(dotted lines). Labels in the lower-left corners represent the amount of
data points used for the inversion compared to the total measured data (same
for resistivity and phase) and the respective percentage root mean square (RMS) deviations of the inversion. (c) Seismic refraction tomogram with main
lithological units including picking percentage (PP) and RMS of the
inversion.
The p-wave velocity structure in the SRT image (Fig. 5c) confirms the presence
of these three units: the shallowest layer, corresponding with the sediment
infill characterized by velocities between 200 and 1000 ms-1,
which is in agreement with values for unconsolidated fine-grained sediments
reported in the literature (Uyanık, 2011); the second layer, where velocities
increase to 1500–2000 ms-1; and depths between 15 and
20 m, where a sudden increase to values >2500ms-1 is
observed. The p-wave velocities of the deepest unit agree with the lower limit
of typical ranges for limestone (Reynolds, 2011), which can be explained by
the high degree of fracturing and dissolution of the karst bedrock. The
seismic velocities of the intermediate layer do not provide any additional
information on its nature but could well be explained by limestone debris or
heavily fractured and dissolved limestone with sediment-filled open spaces.
Profile 3 – comparison of SBP and TDIP corroborates low phase
response of lake sediments
The comparison of the SBP line along the west–east-directed Profile 3 with the
corresponding electrical resistivity images (Fig. 6) confirms the
interpretation of the electrical images: the step in the lower limit of the
sediment layer around 490 m along the SBP profile is also reflected
in the resistivity structure, and it is clearly resolved in the phase
image. Again, the conductive unit extends far below the SBP reflector, in
particular between 440–490 m along the profile. We interpret this
reflector as the contact between pure sediments and the mixed
sediment–collapse debris. Thus, the mixed layer has a lower resistivity than
the superficial fine-grained sediment layer. Along this profile, both
sediment-bearing layers are characterized by low phase values. The
sediment-covered limestone bedrock between 440 and 530 m is
characterized by high phase values, while phase values decrease as this unit
approaches the surface and crops out at the end of the profile. The low phase
values of the limestone outcrop do not fit the previously stated general
characteristics of this unit but might be related to variations in composition
and/or degree of fracturing of the limestone bedrock.
Profile 4 – water-borne TEM and terrestrial TDIP measurements reveal
consistent resistivity models
Figure 7a shows the electrical resistivity image reconstructed from 12 TEM
soundings along the profile crossing Lake Metzabok from west to east. Both
smooth and layered models recover a conductive layer of varying thickness
below the lake floor indicating the presence of fine-grained sediment infill
across the entire basin. This layer only disappears close to the shoreline
(i.e., towards the eastern end of the profile), where the resistive limestone
bedrock is in direct contact with the water body. According to the layered
model, the resistive bedrock itself is encountered at depths of
approx. 15–20 m below the lake bed and only disappears below sounding
MET10, where a possible fracture zone might be responsible for a lower
resistivity at depth.
Geophysical sections along Profile 3 of Lake Metzabok: (a)
sub-bottom profiler section with dashed lines highlighting the main
reflector found below the lake floor, dotted lines outlining a zone of high
diffuse reflectivity including main reflectors and the dashed box showing
the section with TDIP resistivity and phase data; (b) electrical-resistivity
image; and (c) phase image including electrode positions (black dots along
the surface) and lines taken from SBP seismogram. Labels in the lower-left
corners represent the amount of data points used for the inversion compared
to the total measured data (same for resistivity and phase) and the
respective percentage root mean square (RMS) deviations of the inversion.
Geophysical sections along Profile 4 of Lake Metzabok: (a)
interpolated TEM image based on smooth 1D models; left bar graphs show
layered, right bar graphs smooth models, and individual percentage RMS
deviations are given for layered and smooth models, respectively. The black
solid line in the section indicates the water–sediment contact, the dotted
line the top of the limestone bedrock inferred from this image. (b)
Electrical resistivity and (c) phase images including electrode positions
(black dots along the surface), and the main lithological units as
interpreted from the SRT image in (d) (dotted lines). Labels in the lower-left corners of (b) and (c) represent the amount of data points used for the
inversion compared to the total measured data (same for resistivity and
phase) and the respective percentage RMS of the inversion. (d) Seismic
refraction tomogram with main lithological units including picking
percentage (PP) and RMS of the inversion.
At both ends of the profile, and in particular at stations MET1 and MET2, a
conductor is indicated below the resistive bedrock, which could point to a
more fractured bedrock or a lithological contact, e.g., with a shaly
geological unit. However, in the absence of complementary information, such as a
detailed geological map or borehole data, we can also not discard artifacts
due to distorted late-time transient data. Especially close to the shoreline,
where the lake bottom rises steeply, the TEM transients might be affected by
multidimensional effects (e.g., Mollidor et al., 2013), which are not taken
into account by the chosen one-dimensional inverse modeling approach.
Due to the relatively high average resistivity of the subsurface along this
profile, the depth of investigation computed after Spies (1989) and
Yogeshwar et al. (2020) is mostly larger than the 80 m shown
here. Possibly due to the large resistivity and thickness of the limestone
bedrock, no changes of the modeled resistivity have been observed at depths
>80m.
Between stations MET3 and MET7, the TEM image recovers a resistivity
distribution similar to the one of the co-located TDIP profile (Fig. 7b). Taking
into account that the water-borne TEM survey was carried out with an average
of 15 m water column, the consistency with the TDIP resistivity
results from the lake bed clearly indicates the good quality and reliability of
the obtained TEM imaging results.
As observed before, the phase image (Fig. 7c) shows a non-polarizable top
layer, which at a depth of ∼10m is underlain by a unit with a
higher polarization response (absolute phase values around 10 mrad and
higher), corresponding with the debris–sediment unit. The SRT tomogram
(Fig. 7d) shows a sharp increase in p-wave velocity at depths between
20 m (in the western part) and 30 m (in the eastern
part). This southeast-dipping surface correlates with a similar structure in
the TDIP resistivity model, which we again interpret as the contact with the
limestone bedrock.
Geological interpretation of the geophysical survey on Lake Metzabok
The schematic sketch presented in Fig. 8a summarizes our geological
interpretation of the geophysical profiles of Lake Metzabok and the
observations made on the exposed bed of the drained lake (Figs. 4a–d and 8b
and d). The model rests on the assumption that the lakes in the study area are
formed by the coalescence of a number of dolines that resulted from the
collapse of karst cavities. The remains of the collapsed limestone are
expected to have formed a debris layer covering the floor of the former
caves. Subsequently, the fluvial input of fine-grained lake sediments has
first filled up the interspaces between the blocks and then buried the
collapse remains, forming the two uppermost units observed below all
profiles. Figure 8b and c show pictures of such mixed materials exposed on the
surface of the drained Lake Metzabok.
(a) Schematic sketch summarizing the geological conditions below
Lake Metzabok interpreted from the geophysical survey (details not drawn to
scale). The limit between the fine-grained lake sediments and the collapse
debris with sediment-filled interspaces indicated by the white dashed line
stands out as a strong reflector in all sub-bottom profiler images. All
units containing fine-grained sediment are characterized by low electrical
resistivity values; a strong resistivity increase marks the upper limit of
the limestone bedrock as indicated by the red dotted line. Photographs show
(b and c) limestone debris with fine-grained sediment as well as (d)
fractured limestone and fine lake sediments exposed during the low-level
stands in October 2019.
Table 1 summarizes the physical properties of the main units of this
geological interpretation. The electrical resistivity of the fine-grained
sediments and the mixed collapse debris and sediment layer is comprised within
a relatively narrow range. In the TEM and TDIP resistivity images, these two
units may appear as one conductive unit (see red dotted lines in Fig. 8a). It
is not clear why the addition of the more resistive lime stone debris should
decrease the resistivity of the mixed unit compared to the pure fine-grained
sediments. In terms of the phase values, the distinction between these units
is clearer and the increase in the phase response in the mixed layer is
straightforward (because the limestone is more polarizable than the
fine-grained sediments based on our field measurements). The clearest
indication of the inner structure of the conductive unit comes from the
collocated SBP sections, which show a clear seismic reflector at the
corresponding depth. The limestone bedrock becomes detectable by its high
p-wave velocity in the SRT images and its high resistivity (TEM and TDIP),
while its phase response varies over a larger range and is not as
unambiguous. It is worth mentioning that wherever the fine-grained sediments
are underlain by the collapse-debris layer, the limestone bedrock does not
appear as an additional reflector in the SBP sections.
Field measurements on Lake Tzibaná
While the 2019 lake-level decrease left Lake Metzabok (max. depth
25 m) completely drained, the deeper Lake Tzibaná (max. depth
70 m) always preserved a water cover on at least two-thirds of its maximum
surface area. The long N–S-oriented SBP section in Fig. 9 crossing the entire
Lake Tzibaná (Profile 5) shows a similar lake-bottom architecture to the
one derived for Lake Metzabok: steep limestone walls along the shoreline and
flat parts with the typical three-layer structure consisting of fine-grained
sediment cover, collapse debris, and limestone bedrock. Unlike in the case of
Lake Metzabok, the flat parts of Lake Tzibaná are found at two different
levels, which are separated from one another by a steep limestone
cliff. Additionally, the southern part of the profile crosses the delta of the
Nahá river, where we expect a higher fraction of coarser material
(sand and gravel) in the fluvial deposits in comparison to the well sorted
sediments, mainly composed of clay and silt, covering the flat parts of the
lake bottom. In the SBP profile, these delta deposits stand out by a highly
reflective lake bottom, which results in strong multiple reflections between
lake bottom and water surface. Yet, such reflections inhibit the recovery of
any information on the internal structure of the delta.
Ranges of physical properties of the geological units interpreted
from our geophysical profiles and laboratory measurements. Resistivity data
based on TEM, TDIP resistivity, and laboratory measurements. Phase data
(absolute value) according to TDIP images and laboratory data between 1 und
10 Hz; p-wave velocity from SRT images.
Material/geological unitResistivityPhasep-Wave velocity(Ωm)(mrad)(ms-1)Fine-grained sediments5–30<4200–1500Collapse debris and fine-grained sediments5–20>5–61500–2000Limestone bedrock>100>4–5>2000
Long N–S-oriented sub-bottom profiler section crossing the entirety of Lake Tzibaná (Profile 5). The last approx. 450 m roughly coincides with
the TEM section along Profile 6 in Fig. 10a (indicated by the dotted
rectangle). The white dashed lines highlight the main reflector below the
lake floor, which is interpreted as the lower limit of a fine-grained
sediment layer. The white dotted lines enclose the zone of diffuse
reflectivity associated with the collapsed, sediment-filled limestone. The
black dashed line indicates the approximate lake level during the second
field season in October 2019. The last 500 m of the profile correspond to
the delta of the Nahá river, where a high reflectivity of the
sand-covered lake floor results in the occurrence of strong multiples in the
seismogram.
Geophysical sections along Profile 6 of Lake Tzibaná: (a)
interpolated TEM image based on smooth 1D models; left bar graphs show
layered, right bar graphs smooth models, and individual percentage RMS
deviations are given for layered and smooth models, respectively. The black
solid line indicates the water–sediment contact, the dashed line the main
lithological contacts inferred from this image. (b) Electrical resistivity
and (c) phase images including electrode positions (black dots along the
surface) and main lithological units. Red diamonds on the surface indicate
the location of the sediments sampled for laboratory analyses. Labels in the
lower-left corners of (b) and (c) represent the amount of data points used
for the inversion compared to the total measured data (same for resistivity
and phase) and the respective percentage root mean square (RMS) deviations
of the inversion. (d) Seismic refraction tomogram including picking
percentage (PP) and RMS of the inversion, contacts of main lithological
units (white dashed lines) taken from TDIP resistivity image.
The TEM, TDIP, and SRT measurements carried out along Profile 6, which roughly
covers the last 450 m of Profile 5 (see survey layout in Fig. 2b), fill
in this missing information. The resistivity images of both TEM and TDIP
measurements presented in Fig. 10a and b consistently show three main units:
(1) the resistive (>100Ωm) limestone bedrock at depth, (2) a
highly conductive (<10Ωm) clay layer on top, and (3) a layer
of intermediate resistivity (∼30–100 Ωm), in particular
between 200 and 400 m, corresponding to the sand banks and possible
interbedded strata of clay, sand, and gravel associated with the delta
deposits. As observed above along Profile 4, the resistivity model of TEM
sounding TZI41 indicates a conducting unit below the resistive limestone
bedrock, which could be related to a lithological contact, a fracture zone,
distorted late-time data, or multidimensional effects. The low average
resistivity below soundings TZI13–44 result in a significantly reduced depth
of investigation (approx. 55–60 m). The lack of borehole data hinders
a conclusive interpretation of this conductive anomaly at depth.
Probably due to the highly heterogeneous composition of the river delta, these
deposits also show a heterogeneous distribution of phase values (Fig. 10c). As
observed before, the clay and limestone units below the fluvial deposits show
low and high phase values, respectively. The relatively high phase values in
the clay layer below the fluvial deposits are probably inversion artifacts
caused by the relatively noisy TDIP data along this line.
The SRT image (Fig. 10d) shows p-wave velocities as low as
100–200 ms-1 within the fluvial deposits, which are in agreement
with literature values for partially saturated, unconsolidated sand (e.g.,
Barrière et al., 2012). The p-wave velocities increase with depth across the
thick (and probably compacted) clay layer. According to the electrical images,
the surface of the bedrock lies below the lower limit of the SRT
image. Accordingly, the highest velocities of <2000ms-1, seen
in the SRT image, do not reach the high values (>2500ms-1)
typical for limestone bedrock.
DiscussionIdentification of suitable drilling locations
Our geophysical investigations delineate a 5–6 m thick and nearly
undisturbed layer of fine-grained lacustrine sediments covering the flat parts
of Lake Metzabok. Such a layer is relevant for the conduction of
paleolimnological perforations. Suitable drilling locations can be defined
between 450 and 550 m, as well as between 600 and 700 m along
Profile 1 (SBP profile in Fig. 4e). The large variation of the sediment
thickness observed along Profile 3, which is perpendicular to Profile 1,
underlines the need for a comprehensive pre-drilling investigation and an
accurate positioning of the drilling equipment. The sediment layer between 100
and 200 m along Profile 5 represents a suitable drilling location for
Lake Tzibaná (sediment thickness also 5–6 m). Although the deeper
part of Lake Tzibaná is covered by sediments (between 400 and
600 m along Profile 5), too, sediment thicknesses in this part of the
lake are smaller (only 3–4 m according to the SBP image) and drilling
efforts would be considerably higher, due to the larger water column at this
location (approx. 30 m during water-level high stand in 2019).
With a thickness of >40m according to our electrical imaging
results, the sedimentary cover along Profile 5 of Lake Tzibaná
(particularly between 250 and 400 m) is much thicker than the
sediments covering the flat parts of both lakes. However, our results also
indicate that these sediments rather correspond to fluvial deposits of the
river delta. In this depositional regime, we expect much higher rates of
sedimentation and thus not necessarily an older paleoenvironmental record.
Additionally, river deltas are much more dynamic systems, in which sediments
are deposited, eroded, and redeposited repeatedly, which decreases the
probability to obtain undistorted sediment records as encountered farther
offshore.
Geological situation of the studied lakes and hydrogeological
implications
Our field observations and geophysical imaging results also have important
implications for the general understanding of the geological situation of the
two studied karst lakes: large areas of both lakes are covered by a layer of
clayey sediments, which have a low hydraulic permeability. Thus, where this
layer is thick enough (up to 5–6 m across large areas), it acts as a
hydrological barrier between the lakes and the underlying karst. However, the
remaining heavily fractured and uncovered limestone outcrops (e.g.,
Fig. 8b–d) effectively connect the lakes with the karst water system. This
conclusion is underscored by the high velocity at which the two lakes drained
practically simultaneously between February and July 2019. Accordingly, the
sudden drainage of both lakes might be related to the same hydrogeological
process.
Methods used to image the sub-bottom structure of the studied
lakes. Summary of physical properties resolved, typical parameter ranges in
the study area, and setup and characteristics of the measurements.
Typical depths of investigations (DOIs) depend on the specific instrumental setup
used; main contributions and limitations mostly refer to the present study
and the specific geological situation.
MethodPhysical property and typical rangeSetup and characteristicsDOI (m)Main contributionMain limitationsSBPvpa only reflection patterns resolvedWater borne; 10 kHz transducer, 300 W output power, boat10Resolves contact between fine-grained sediments and underlying mixed layer (e.g., Fig. 4e)– Penetration depth ≤10m below lake bottom (e.g., Fig. 4e) – No penetration in coarse delta sediments (e.g., Fig. 10a)TEMρb 5–500 ΩmWater borne; unanchored single-loop system, 412 m2 loop area, 1 A transmitter current, rubber boat50–100Delineates top of bedrock (e.g., Fig. 7a) and coarse delta deposits(e.g., Fig. 10a)– Low acquisition velocity/productivity compared to SBPTDIPρ 5–500 Ωmφc 2–6 mradTerrestrial; 5–10 m spacing, 48 electrodes, dipole–dipole, 0.5–1 A transmitter current, 500 ms pulse50–70ρ: delineates coarse delta deposits (e.g., Fig. 10b) φ: improved delineation of fine-grained sediments (e.g., Fig. 5b)– No clear distinction between lake sediments and limestone bedrock if only ρ is considered (e.g., Fig. 4f)SRTvp 200–3000 ms-1Terrestrial; 5 m spacing, 24 geophones (28 Hz), energy source: 7.5 kg sledgehammer40–50Delineates top of bedrock (e.g., Fig. 7d)– Eventually low quality of data acquired on muddy lake floor
ap-Wave velocity. b Electrical
resistivity. c Resistivity phase.
While the interconnectivity between surface water and karst aquifer is well
documented by field observations and further supported by the interpretation
of our geophysical results (see Fig. 8), the specific cause(s) and
mechanism(s) of the sudden drainage of Lakes Metzabok and Tzibaná remain
unrevealed. The suddenness of the drainage suggests that one or more
previously clogged karst conduits were unplugged around these dates. Planned
time-series analyses of hydrological and meteorological data in combination
with paleoenvironmental studies on sediment cores will possibly provide more
detailed insight into the mechanism and its triggers and thus shed light on
the question of whether such catastrophic drainage events as the one observed
during 2019 are linked to recent climate change or another geodynamic process.
Lessons learned from implementing a multi-methodological approach for
lake-bottom reconnaissance
Only the combination of complementary methods employed in the present study
allowed us to produce comprehensive geological models of the lake-bottom
geology of the studied karst lakes. Table 2 summarizes the characteristics of
the four field methods (SRT, TEM, TDIP, and SRT), the individual contributions
of each method, and their respective limitations identified in this study. In
the following, we will discuss some important aspects of this overview in more
detail.
Sub-bottom profiler reflection seismic method
For shallow-water applications, the compact and mobile experimental setup of
the SBP technique offers clear advantages. Additionally, the high productivity
and resolution in combination with the straightforward interpretation of the
SBP seismograms evidence that such reflection seismic methods are best suited
for a first reconnaissance of the lake bottom. In comparison, water-borne TEM
measurements are by far slower and more labor intensive (for both data
collection and processing) and the resulting imaging results have a lower
lateral resolution. In our study, the contact between fine-grained clay
sediments and the underlying mixed layer (collapse debris and sediment) was
clearly visible from the SBP data, which permits a straightforward estimation
of sediment thicknesses along SBP survey lines. The contact or transition
between mixed layer and limestone bedrock was also noticeable in the SBP
images, but the interpretation was not as clear as in the case of the first two
layers and mainly built on the availability of complementary TEM and TDIP
data. The main limitations of the SBP survey consist of the low depth of
penetration of this method, which hardly reached 10 m below the lake
bottom, and of the total lack of sub-bottom information as soon as the lake bed
is covered by coarser sediments as observed in the deltaic region of Lake
Tzibaná. Such “opaque seismic facies and high […] reflectivity” of
fluvial sediments have been discussed before by Orlando (2013) for
measurements on the river Tiber in central Italy. Hence, the combination of
waterborne TEM and SBP methods could offer a solution to improve the
investigation of deep areas (resolved by TEM data), while lateral information
can still be gained using SBP. The inclusion of SBP information for the
interpretation of TEM data towards the inversion of an improved resistivity
model is an open area of research.
Water-borne transient electromagnetic method
The water-borne TEM sounding system developed for this study turned out to
provide reliable resistivity images for water depths down to at least
20 m. This conclusion is supported by the agreement of the
resistivity images obtained from water-borne TEM and lake-floor TDIP
measurements along both TEM profiles (Figs. 7 and 10). Previous shallow-water
TEM studies (e.g., Butler, 2009, and references therein; Hatch et al., 2010;
Mollidor et al., 2013) employed in-loop configurations with an outer
transmitter loop and a smaller receiver loop or coil in the center, while we
used a light-weight single-loop configuration, which is quicker to assemble
and easier to handle while navigating on the lake. It is worth mentioning that
in terms of noise level and depth of investigation, our simple system
consisting of one single circular loop provides results comparable to those
obtained with more sophisticated systems consisting of separated transmitter
and receiver square loops (e.g., Yogeshwar et al., 2020).
Besides the use of a single-loop configuration, the use of small loops as
employed in the present study can eventually result in distortions in the
transient data. The measured curves (truncated to 21.4–174.5 µs)
do not show any conspicuous features (see data example in the Appendix) and
can be adjusted by reasonable resistivity models with an overall low
root-mean-square (RMS) deviation. Thus, we discard the presence of adverse
effects in our data set. The good agreement between TEM and TDIP-derived
resistivity models along collocated survey lines further supports this
conclusion.
In the present study, TEM resistivity images clearly delineate the top of the
bedrock and reveal the inner structure of the deltaic deposits of the river
Nahá, which are not resolved by the SBP seismograms. The interpretation of
the layered resistivity structure below the flat parts of the lake bottom is
only possible by combining TEM resistivity images with complementary
information from other methods. In particular, the SBP seismograms (and TDIP
phase images) imply that the thickness of the fine-grained lake-bed sediments
does not exceed 5–7 m in Lake Metzabok, while conductive units extend
down to depths of 20–30 m (below the lake bottom) and more. We
resolve this apparent contradiction by postulating an intermediate layer made
of limestone debris from collapsed karst cavities and fine-grained sediments
filling the spaces between the limestone blocks. This mixed layer seems to be
characterized by a much higher seismic velocity compared to the fine sediments
but a similar or slightly lower electrical resistivity. Consequently, the
small resistivity contrast between the fine-grained lake-bed sediments and the
underlying mixed layer hinders an unambiguous estimation of sediment thickness
from TEM (and TDIP) resistivity data alone.
Our results also show the advantages in the interpretation of the sounding
data after the incorporation of water depth and eventually water resistivity
into the inversion of TEM data as a priori information. Water depth is readily
measured during the TEM sounding using a standard echo sounder. Further
investigations can consider the addition of fluid conductivity and temperature
measurements using conductivity–temperature–depth (CTD) probes to improve the
inversion of waterborne measurements and, thus, the investigations of the
lake bed by electrical methods. Such information can also be obtained from the
analysis of water samples.
We have adjusted smooth and layered models to the TEM sounding data, both
recovering similar sub-bottom structures along the two lines discussed here.
While the smooth models facilitate a direct comparison with the (smooth) 2D
TDIP resistivity images, the layered models are more appropriate to locate
sharp geological contacts. The average fit quality (as assessed by the
percentage RMS), which is slightly better for the layered models, could point
to rather sharp contacts. However, it is not at all straightforward to decide
whether sharp resistivity contrasts exist between the main lithological units
(i.e., sediment cover and limestone) or not. As our interpretation of the
Metzabok data suggests, e.g., within the mixed layer, there might be a smooth
transition due to a continuously increasing volume content of limestone with
depth. The same is true for contacts between different, eventually interbedded
sedimentary units (e.g., fine-grained lake sediments or sandy delta deposits).
Induced-polarization imaging of the lake floor
The fact that the studied lakes drained provided us with the unique
opportunity to carry out TDIP measurements directly on the lake floor. The low
contact resistances and the easy installation of electrodes on the soft ground
represent ideal conditions for electrical imaging measurements. Furthermore,
the evaluation of both phase data for sediment samples analyzed in the
laboratory and for the in situ measurements on the exposed lake floor is
unprecedented or at least very rare in geophysical literature. In the present
study, the TDIP phase results permitted the obtained
geological model of the lake bottom to be significantly improved. In particular, the IP images showed a low
phase response of the lake sediments on one hand and a comparably high phase
response of the limestone bedrock and the collapse-debris layer on the other
hand. The interpretation of the field TDIP phases is sustained by our
laboratory measurements on sediment samples and the good overall agreement of
the shallow low-phase layer with the corresponding reflector in the SBP
images.
Larger variations in the phase response of sediments (especially the increased
phase values of sample TZI19-A) are likely related to different depositional
regimes: preliminary geochemical analyses of the sediment samples imply a
significant increase in total organic carbon (TOC) and the carbon-to-nitrogen
ratio (C/N) of the sample TZI19-A compared to the other five samples
(Philipp Hoelzmann, personal communication, 2020). High values of TOC and C/N point to a larger fraction of organic
matter from terrestrial sources in sample TZI19-A, while the smaller amount of
organic matter of the other five samples probably stems from algal plants. A
strong control of TOC on the phase response has been reported earlier for
other materials (e.g., Schwartz and Furman, 2015; Flores Orozco et al., 2020).
Based on the encouraging findings of the present study, the application of
TDIP imaging for the lake-bottom characterization emerges as an interesting
complementary method for the characterization of lake-bottom sediments.
Although promising for desiccated or shallow lakes, there are some limitations
for TDIP measurements carried out on water-filled lakes: in principle,
TDIP data could be collected with floating electrode arrays as used for
water-borne direct-current resistivity surveys. However, the collection of
deep IP data – as needed to investigate the sediments below a water column
of, e.g., 20 m – often suffers from a low S/N ratio. This
limitation could be overcome by bringing the electrodes closer to the lake
bottom, which is possible but logistically more effortful (e.g., Baumgartner
and Christensen, 2006).
Seismic refraction tomography of the lake floor
In the present study, the land SRT measurements carried out on the exposed
lake floor confirmed the layered structure of the flat parts of the bottom of
Lake Metzabok inferred from the preceding three methods. In those cases, where
the depth of investigation of the SRT images was large enough to cover the top
of the limestone bedrock (i.e., Profiles 2 and 4), this geological contact was
delineated clearly by a steep increase in the SRT velocity model. The main
limitations regarding the applicability of SRT measurement on the lake floor,
which we identified in this study, are related to the specific surface
conditions: on the one hand, the generation of seismic pulses was excessively
labor intensive, as the steel plate bogged down into the soft lake bottom and
had to be dug out after every single hit. On the other hand, the low
signal-to-noise (S/N) ratio of some data collected on the muddy lake floor
(e.g., along Profile 2; see Appendix), rendered the processing and
interpretation of SRT results challenging. We attribute the low S/N to the
difficult coupling of seismic energy into the ground, a high energy loss of
seismic signals in soft sediments, and a higher level of ambient noise (e.g.,
induced by wind). Although the picking percentages of noisy SRT profiles
(here, Profile 2) were much lower and RMS deviations significantly increased
in comparison to data collected on firm ground (e.g., Profile 5), the depth of
investigation only decreased by approx. 20 % (see Figs. 5c and 7d).
Conclusions
Based on the combination of different geophysical techniques, the present
study provides important insight into the geological situation of two
hydraulically highly dynamic karst lakes. The comparison of water-borne and
land surveys (carried out after the sudden drainage of the lakes) permits a
detailed evaluation of the potential and limitations of different seismic,
electrical, and electromagnetic geophysical methods for the investigation of
such lakes. One principal outcome of this study is that only the combination
of complementary methods provides sufficient information to develop a
comprehensive geological model of complex karst environments. In this sense,
the present systematic field study paves the way towards an improved
geophysical characterization, which is needed to better understand
surface–groundwater interactions in karst systems and, more importantly, to
evaluate climate-change-related effects on karst water resources. In this
regard, the interpretation of our results permitted suitable
drilling locations to be determined for future paleoenvironmental drilling campaigns, which are
characterized by thick (5–6 m), undisturbed, fine-grained lake
sediments covering the flat parts of both studied lakes. The recovery of
continuous and far-reaching sedimentary records is another important element
for the understanding of the impact of climate change on the availability and
quality of water in karst systems.
The possibility to recollect additional data directly on the exposed lake
floor after the sudden drainage of Lakes Metzabok and Tzibaná
substantially benefitted the evaluation of the different methods. The good
agreement of electrical resistivity data collected with a new water-borne TEM
system, TDIP resistivity data from the dry lake bottom, and electrical
measurements on sediment samples in the laboratory demonstrates that the new
TEM system works well down to water depths of at least
20 m. Furthermore, there is no reason to assume that the system should
not work as well in even deeper water (>20m) depending on the
water conductivity. TDIP phase images turned out to provide relevant
complementary information – here, in particular about the inner structure of
the conductive units covering the lake bottom. Seismic data from a water-borne
SBP and a SRT survey on the dry lake floor provided complementary information
and allowed the interpretation of the two conductive units as a top layer of
fine-grained sediments and an intermediate layer of debris from collapsed
cavities in the heavily karstified limestone bedrock. At the same time, the
delineation of the upper limit of the buried limestone bedrock was not
possible from the seismic data alone. Thus, the final interpretation was only
possible by combining electrical and seismic data sets and by incorporating
geological and geomorphological constraints, showing – once again – the
strength of a multi-methodological and interdisciplinary approach.
Data quality and filteringTEM
Figure A1a shows the TEM raw data of selected soundings along Profile 6
of Lake Tzibaná in terms of the induced voltage (normalized to loop area
and transmitter current). As described in the main text, all sounding curves
were truncated to a unit time window between 21.4 and 174.5 µs. Earlier times were ignored to minimize the effect of distorted early-time
data. At the latest time window, the SEM of the induced voltage is
approximately 5×10-9VAm-2 for all soundings (except
for TZI44) and about 1–2 orders magnitude smaller than the corresponding
induced voltage. Figure A1b shows the measured and calculated apparent
resistivity curves of the same soundings. As indicated by the overall small
root-mean-square error (RMSE < 5 %), the measured curves are all
recovered well by the adjusted smooth resistivity models, which are visualized
in Fig. 10.
TDIP
TDIP data were filtered based on the apparent resistivity and apparent
chargeability data. In a first step, TDIP readings with apparent resistivity
values ≤0Ωm and/or apparent chargeability values ≤0mVV-1 were removed as outliers. In a second step, based on the
visual assessment of the raw-data pseudo-sections and histograms (see Fig. A2
for an exemplary data set), measurements with apparent chargeability values >8mVV-1 were removed as further outliers. The selection of the
limit of 8 mVV-1 for the apparent chargeability values is based
on the observation of a narrow distribution of physically meaningful values in
the corresponding histograms (see Fig. A2d and h). In the case of the data set
shown in Fig. A2, which corresponds to the second part of the roll-along
Profile 1 of Lake Metzabok, this filtering results in a reduction to
57 % of the unfiltered data set. This high loss of data is related
to the comparably poor data quality of the chargeability measurements along this
long line (470 m length, 10 m electrode spacing). Shorter
profiles with half the electrode spacing (5 m in the case of profiles
2–4 and 6) are less affected by noisy chargeability data as reflected in a
higher percentage of useful data (up to ∼88% in the case of
Profile 3 of Lake Metzabok).
SRT
Collected with 24 geophones and 25 shot positions, each tomographic data
set consists of a total of 600 seismic traces. Figure A3 shows exemplary
seismic traces for one-central-shot positions and the travel-time curves
(constructed from the picked first arrivals of all 25 shot positions) for one
relatively noisy (Profile 2) and one relatively clean (Profile 4) data
set. The picking percentage displayed along with the travel-time curves
reflects the number of traces for which a first arrival could be identified
and serves as a measure of overall data quality. The low data quality of
Profile 2 data results in a low picking percentage (341 out of a total of 600
traces) and mainly affects long-offset data, which clearly reduces the depth
of investigation (∼40m, Fig. 5c). In comparison, SRT data
collected along Profile 4 are cleaner (552 first out of 600 first arrivals
picked) and, thus, result in a larger depth of exploration (>50m,
Fig. 7d).
(a) Induced-voltage
data of selected TEM soundings along Profile 6 of Lake Tzibaná. Induced
voltages are normalized with the injected current and the loop area. The mean
values of the stacked signal per time gate are shown in blue (circles), the
standard error of the mean in red (squares). Dashed lines indicate an almost
constant (exception: sounding TZI44) late-time error level of
5×10-9VAm-2 (horizontal
lines) at 174.5 µs (vertical lines). (b) Observed (blue circles)
and calculated (red squares) apparent resistivity curves of the same TEM
soundings. The root-mean-square (RMS) errors of the individual model fits are
indicated, too. The corresponding inverted models (smooth models with 20 layers) are visualized in Fig. 9.
Apparent resistivity and apparent chargeability pseudo-sections (a, c, e, g) and histograms (b, d, f, h) of the TDIP measurement
corresponding to the second part of roll-along Profile 1 of Lake Metzabok.
The first two lines (a–d) show the unfiltered raw data set consisting of
1308 individual measurements; the last two lines (e–h) visualize the
remaining 747 measurements after the application of the filters described in
the main text.
Exemplary seismic traces (wiggle traces with variable
density plots in the background) corresponding (a) to Profile 2 with a high
noise level and (b) to Profile 4 with a much lower noise level. As a direct
result of data quality, the travel-time curves (c) of Profile 2 (picking
percentage 57 %) are much less populated than those (d) of Profile 4
(92 %). The loss of information particularly affects late travel times and
thus significantly reduces the depth of investigation along noisy profiles.
Data availability
All raw and processed data of this study (and some additional data not
discussed here) are available at Zenodo
(10.5281/zenodo.3782402, Bücker et al., 2020) along with the MATLAB scripts used
to prepare the visualizations presented in this paper.
Author contributions
AFO, JG, JH, WM, EG, and JR participated in the field seasons, which were
planned and coordinated by MB, LP, AFO, CP, AH, and AS. RG and JH were
responsible for the sediment and water samples and the laboratory IP data.
CP, EG, and JR processed the SBP data. AFO processed and inverted the TDIP
data, MS the SRT data, and LA the TEM data. WM made a geological field
survey and gave insights into the geological context. JB prepared the maps
and participated in the geological contextualization. All authors
participated in the interpretation and discussion of the results. MB lead
the redaction of the paper with contributions of all co-authors.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
We thank the Comisión Nacional de Áreas Naturales Protegidas
(CONANP) and the authorities of the protected area Nahá and Metzabok, in
particular Sergio Montes Quintero, Santiago Landois Álvarez Icaza,
Miguel García Cruz, Rafael Tarano, and José Ángel
Solórzano, as well as the municipalities of Nahá and Metzabok for
their openness and friendly support. We are grateful for the help provided
by Mauricio Bonilla, Johannes Bücker, Martín Garibay, Carlos Cruz,
Roberto Reyes, Lorena Bárcena, Rodrigo Martínez Abarca, and
Theresia Lauke, and all other colleagues and students, who were actively
involved during the field seasons. Finally, we would like to thank Socorro
Lozano, Margarita Caballero, Beatriz Ortega, Sergio Rodríguez, and Alex
Correa Metrio from the Institutes of Geology and Geophysics, UNAM, for
institutional and logistical support.
Financial support
This research has been supported by the Consejo Nacional de
Ciencia y Tecnología (grant no. 252148), the Deutsche
Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 439783529, the Austrian
Science Fund (grant no. FWF-I-2619-N29), the Agence Nationale de la Recherche
(grant no. ANR-15-CE04-0009-01), and the Austrian Federal Ministry of Science,
Research and Economy (grant no. ExploGRAF). This open-access publication was funded by the German Research Foundation and the Publication Funds of Technische Universität Braunschweig.
Review statement
This paper was edited by Ulrike Werban and reviewed by Pritam Yogeshwar and one anonymous referee.
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