The phrase
Characterizing subsurface flow is the aim of many hydrological field and
modeling studies. In hillslopes with steep slopes and structured soils,
subsurface flow is controlled by high gradients and high heterogeneity of
hydraulic properties of the soil, resulting in a highly heterogeneous flow
field and preferential flow paths
In previous studies at the hillslope scale, the focus was often on lateral
flow processes and the establishment of overall connectivity. Hillslope-scale
excavations yield information on spatial extent and characteristics of
preferential flow paths in 3-D
In recent years, a trend towards non-invasive methods for hillslope-scale
observations has emerged
Especially in structured soils, where subsurface flow is likely dominated by preferential flow paths, methods are required which are capable of covering the existing heterogeneity. Point measurements and integrated observations alone are barely able to meet this requirement. Structural changes of the subsurface as revealed by difference images obtained from GPR measurements, in contrast, reveal spatially discrete flow paths. We therefore applied and tested time-lapse GPR measurements to investigate subsurface flow processes within a hillslope with shallow and highly structured soils.
We chose a combination of conventional hydrological methods and non-invasive
GPR measurements to explore flow processes by means of observations at the
hillslope
All methods and experimental results were subsumed under the framework of
form and function as shown in Fig.
The concept of form and function applied to observations in hillslope hydrology. Four different categories which can be applied to data as well as the data sources.
In our case, form includes all static properties and spatial structures, such
as topography, geology, and subsurface structures, but also porosity,
hydraulic conductivity, and stone content of the soil. Function summarizes
all dynamics and processes, including soil moisture dynamics, discharge
behavior, and preferential flow. These two are closely related and co-evolve.
Based on this idea,
Starting on the left side of the spectrum presented in
Fig.
Following the form and function framework, the hypotheses focus on the
potential of response observations for hillslope hydrological field research
and the application of time-lapse GPR measurements in this context. Response observations (discharge, TDR and GPR data) are sufficient to
characterize subsurface flow within the hillslope. (function described without form) Response patterns can be used to deduce flow-relevant structures in the
subsurface. (function reveals form) Time-lapse GPR measurements visualize subsurface flow dynamics and
patterns and can replace hillslope trenches.
The investigated area is located at the south-eastern edge of the Ardennes
Massif in western Luxembourg. It consists of a number of nested
sub-catchments of the Colpach River catchment, which is part of the Attert
River basin. The landscape of this area is characterized by Devonian schist
bedrock
The schist bedrock below is strongly inclined, with almost vertical
foliation, and is considered impermeable but with fractures which can
function as a complex flow network with local storage in the rock cracks when
saturated
Within this landscape, a typical hillslope consists of agriculturally used
elevated plateaus and forested valleys with steep slopes
(15–25
The average annual precipitation between 2011 and 2014 was 965 mm; the
annual average air temperature was 8.8
The experimental work conducted in the framework of this study focused on a
north-facing hillslope in the Holtz headwater catchment. The experiment was
supplemented by hydrological data from five neighboring headwater catchments
of different sizes. All sub-catchments as well as the location of the
irrigation site are shown in Fig.
The experimental approach consists of two parts. The hillslope-centered approach concentrates on local observations at the hillslope. It includes soil moisture profile measurements and 2-D GPR measurements, pore water and piezometer isotope data, and measurements of surface runoff. These data were collected during a natural summer storm event on 20 June 2013 and a hillslope-scale irrigation experiment 1 day later on 21 June 2013.
The stream-centered approach focuses on the discharge response and stream
water stable isotope signal during the same summer storm event as mentioned
above. The stream-centered approach focuses on the integrated response of a
catchment. While hydrographs and stream tracer dynamics have been studied and
discussed extensively elsewhere
Map of the investigated Colpach River catchment and the four gauged sub-catchments. The site of the hillslope-scale irrigation experiment is located in the Holtz 2 catchment and is indicated in red.
The hydrological response behavior of several nested sub-catchments was investigated. At four locations v-notch or trapezoidal gauges were installed and equipped with pressure transducers, measuring water level, electric conductivity, and temperature (CTD sensors, Decagon Devices Inc.). Water levels were measured every 15 min. Precipitation was monitored with tipping buckets (Davis Instruments Corp.) in the Holtz 1 headwater. All data were logged with CR1000 data loggers (Campbell Scientific Inc.).
At the same locations and additionally close to the source of the Holtz River
(Holtz 1 in Fig.
Experimental methods applied in the stream-centered and hillslope-centered approaches, divided into the sampling during the natural rain event and the irrigation experiment. Additionally, some structural background information was obtained from the literature and a digital elevation model.
In addition to the stream water, rainfall water was sampled. Bulk samples
were collected during the rainfall events right next to the experimental
site. The water from the saturated zone was manually sampled on a monthly
basis over the course of 1 year from piezometers close to the sub-catchment
gauges. Samples were taken with a peristaltic pump from fresh water flowing
into the piezometers, after they had been pumped empty (Fig.
To calculate the event water contribution, we applied a simple hydrograph
separation
Vertical cross section
The plot of the hillslope-scale irrigation experiment was located on the
bottom 8–13 % of the 238 m long investigated hillslope, which was
defined by a slope of more than 6
Four circular irrigation sprinklers (Wobbler, Senninger Irrigation Inc.) were
arranged in a 5 m by 5 m square in the upper part of the experimental
site (Fig.
The surrounding area functioned as a buffer of about 4 m with less intense
irrigation, thus mitigating boundary effects. A rain shield defined the lower
boundary of the core area as a sharp transition to the non-irrigated area
below. The water from the rain shield was collected with a gutter and routed
away from the investigated area. The overall irrigation area (including core
area and buffer) covered
To monitor the irrigation, we used a flow meter at the main water supply of the irrigation system to measure the absolute water input. Furthermore, one tipping bucket was used to quantify the temporal variability of applied irrigation, and 42 mini rain collectors, evenly distributed across the core area, covered the spatial distribution of the irrigation amount. The topography of the experimental site as well as all devices and installations were mapped with a total station (Leica Geosystems AG).
The experiment took place on 21 June 2013. After 1 week of dry weather, two
natural rainfall events of 20.2 and 21.2 mm occurred on 20 June. The first
one had a mean intensity of 2.9 mm h
The monitoring of hydrological processes during and after the irrigation period was accomplished with a combination of methods: a dense array of soil moisture profiles for time domain reflectrometric (TDR) measurements arranged as diverting transects along the slope line, and four GPR transects located downhill of the core area and oriented parallel to the contour lines and the rain shield for time-lapsed GPR measurements. The latter yielded vertical cross sections of the subsurface.
A surface runoff collector was installed across 2 m at the lower boundary of the core area. Surface runoff was collected by a plastic sheet installed approximately 1 cm below the interface between the litter layer and the Ah horizon of the soil profile and routed to a tipping bucket.
An array of 16 access tubes for manual soil moisture measurement with TDR
probes (Pico IPH, IMKO GmbH) covered the depth down to 1.7 m below
ground. The layout consisted of three diverging transects with four TDR
profiles in the lower half of the core area, the highest density of profiles
just downslope of the rain shield, and the furthest profile about
9 m downhill (Fig.
Soil moisture was measured manually. To increase the temporal resolution of
the measurements, three probes were used in parallel. While these probes were
identical with regard to measuring technique and manufacturing, they differed
slightly in sensor design: two TDR probes had an integration depth (i.e.,
sensor head length) of 0.12 m, and one probe had an integration depth of
0.18 m. These sensors were manually lowered to different depths into the
16 access tubes, where they measured the dielectric permittivity of the
surrounding soil in the time domain through the access tubes. Given a mean
penetration depth of 5.5 cm and a tube diameter of 4.2 cm, this yields
an integration volume of
In addition to the hydrological methods, GPR was used to monitor the shallow
subsurface. Two-dimensional
time-lapse GPR measurements were conducted along four transects across the
downhill monitoring area. The transects had distances of
The GPR system consisted of a pulseEKKO PRO acquisition unit (Sensors and
Software Inc.) equipped with shielded 250 Mhz antennas. The data were
recorded using a constant offset of 0.38 m, a sampling interval of
0.2 ns, and a time window of 250 ns. For accurate positioning, a kinematic
survey strategy was employed. The positioning was based on a self-tracking
total station (Leica Geosystems AG), which recorded the antenna coordinates
as described by
The stable isotope sampling included samples taken from five soil cores (pore
water), piezometers (percolating pore water), as well as irrigation and rain
water (input water). The soil cores were taken with a percussion drill with a
head diameter of 7 cm and split into 5 cm increments to get depth
profiles of the stable isotopic composition (
At the locations of the pre-irrigation soil cores, piezometers were
installed. Additionally, three more piezometers were installed at a depth of
The soil samples were prepared following the direct equilibration method as
proposed by
Almost 5000 individual soil moisture measurements were taken during the
irrigation experiment. As the three TDR probes had different integration
depths (0.12 and 0.18 m), the measurements had a different depth offset
relative to the ground surface when referenced to the center of the probe,
and had to be aligned. To do so, the measurements, which were originally
taken in 0.1 m increments, were resampled at depths by linear interpolation.
Due to the potentially short correlation length of soil moisture
All TDR measurements were referenced to the last measurement before
irrigation. The resulting data set of relative soil moisture changes
The time-lapse GPR survey comprised repeated recordings of vertical 2-D GPR
data along the four transects. The data processing of each measurement relied
on a standard processing scheme, including bandpass filtering, zero time
correction, exponential amplitude preserving scaling, inline fk-filtering,
and a topographic migration approach, as presented by
There is no standard interpretation procedure for the analysis of time-lapse
GPR data. Most approaches are based on calculating trace-to-trace differences
The calculated structural similarity attributes are a qualitative indicator of relative deviations from the reference state. The GPR data indicated remaining water from the natural rain event when the experiment was started. Therefore, the last acquisition time 24:00 h after irrigation start was chosen as the reference time for all GPR transects. Based on the assumption that the reference state is the one with the lowest water content, decreasing structural similarity was interpreted as an increase in soil moisture.
To convert GPR two-way travel time (TWT) into depth, we used the average
measured GPR propagation velocity of 0.07 m ns
To interpret the structural similarity attribute images, we discriminated between the signal of the natural rain event and the irrigation. The discrimination was based on the temporal dynamics of each pixel of the GPR transects (i.e., every single value in the matrix of distance along the GPR transect and depth/TWT). The first GPR measurements were taken 12:52 h after the end of the second rainfall event (i.e., 6:30 h before irrigation start) and the observed responses were attributed to the natural rain event. Once the structural similarity attribute value of a pixel decreased more than 0.15 after irrigation start, the signal of that pixel was attributed to the irrigation. The threshold of 0.15 was chosen based on the noise of the last measurement 18:00 h after irrigation start and exceeds the standard deviation of that measurement by a factor of 3. The same procedure was applied to infer the time of first response to the irrigation signal, which was used to calculate response velocities.
This procedure yields 2-D maps of response patterns, with each pixel being attributed to either the irrigation or the natural rain event. The structural similarity values are a semi-quantitative measure of soil moisture and thus no reliable indicator to directly compare actual soil moisture responses recorded at different locations or at different times. We therefore used the areal share of the monitored cross sections to compare the impact of the two input events. To do so, all pixels of one of the two categories (natural rainfall or irrigation) which fell below the value of 0.85 (i.e., maximum similarity 1 minus threshold 0.15) were counted and expressed as a fraction of the entire cross section. The resulting areal share does not represent the actual share of activated flow paths, but is a semi-quantitative indicator of the hillslope cross section impacted by active flow paths.
As no tracers were used for irrigation, dynamic processes had to be inferred from changes in state. For TDR measurements, the time of first response was defined as an increase in soil moisture by 2 % vol relative to initial conditions. This threshold was chosen based on the standard deviation of measurements under presumably constant conditions. The time of first response was identified for each TDR profile and depth increment.
Due to the experimental setup, soil moisture dynamics on the core area were dominated by vertical processes, while lateral processes controlled the dynamics at the downhill monitoring area. Accordingly, vertical and lateral response velocities were calculated from core area and downhill monitoring area TDR profiles, respectively.
As a continuous wetting of the soil profile could not be assumed, all response velocities were calculated for the entire depth (or distance) instead of depth increments. Response velocities are therefore integrated values describing processes in the entire soil column above. This procedure also accounts for heterogeneous processes and preferential flow paths, which may bypass shallower depths without leaving a detectable soil moisture signal.
Lateral response velocities account for the depth and distance between soil
surface at the rain shield and TDR profile in question and, therefore,
integrate lateral and vertical flow. They were calculated for every depth of
the soil moisture profiles at the downhill monitoring area. The time of the
very first response signal measured on the core area was used as reference
time
The same holds true for the lateral response velocities calculated from GPR
data. In accordance with the separation of the natural rain event signal and
the irrigation signal, the first decrease in structural similarity of more
than 0.15 was interpreted as the arrival of the irrigation signal. Single
structures and flow paths are not the focus of this article and will be
discussed in the companion study by
The figure shows the natural storm event on 20 June 2013 in the
Colpach River catchment and the local intensity of the irrigation on
21 June 2013. The hydrographs below show the discharge response of four
nested catchments (solid lines), in combination with the dynamics of the
In response to the summer storm event just before the hillslope-scale
irrigation experiment, all gauged sub-catchments showed double-peak
hydrographs, with one immediate short peak, and one prolonged peak delayed by
several hours (second rainfall event, Fig.
A simple mass balance calculation revealed that the first peak constituted
7.5 % of the total event runoff at gauge Holtz 2. The total event runoff
coefficient was 0.44. Referenced to the precipitation amount, about
3.3 % of the input left the headwater within 7:00 h after the rain
event (Table
The
Uncertainty in hydrograph separation was caused by the uncertainty of the stable isotopic composition of the precipitation input. The uncertainty due to spatial variability of the precipitation input was kept minimal for Holtz 2, by sampling the precipitation within the small catchment (45.9 ha). While we could not sample the isotopic input at high temporal frequency, the bulk sample of the precipitation data represents a weighted average of the input isotopic signal.
The 2-D time-lapse GPR measurements yield images of structural similarity
referenced to the last measurement, which were taken 24:00 h after
irrigation start, which translates to 43:22 h after the second natural rain
event. The first GPR measurements were taken about 12:52 h after the second
rain event and can be interpreted as the subsurface response patterns of this
event (Fig.
While transect 1 showed only a weak signal of the natural event in the first
measurement, transects 2 and 3 exhibited stronger and longer lasting signals.
The areal share of active regions of the four transects in the measurement
preceding the irrigation experiment was 38.5, 51.6, 64.4, and 50.5 % from
upslope to downslope. Except for transect 2, which even showed a slight
increase in the areal share of active regions between the first and second
measurements, the signal of the natural rain event was continuously vanishing
(Fig.
The irrigation intensity was relatively constant over time, with only weak
fluctuations due to gradual clogging of the intake filter. The spatial
distribution of the irrigation intensity on the core area was influenced by
the sprinkler setup and the slope of the experimental site. The mean
intensity on the core area was 30.8
The core area mass balance is shown in Fig.
Water balance of the top 1.4 m of the soil column for the four core area TDR profiles. Dashed lines indicate the storage increase at the last measurement before irrigation ended. The variability between the four profiles shows the high heterogeneity and causes uncertainty regarding the average mass balance of the core area.
The soil moisture data measured at the TDR profiles at the irrigation site, showing the soil moisture dynamics in depth. The top four plots show all four core area profiles; columns are arranged according to the three diverging transects in the downhill direction. Rows are approximately at the same contour line. Measurements were taken at 0.1 m increments. While data analysis was based on non-interpolated data, soil moisture measurements were here interpolated linearly for better visualization. The plots cover the time from irrigation start until 9:00 h after irrigation start to focus on the first soil moisture response. Arrows indicate the measurement times and installation depth of each TDR profile. Time is given in hours after irrigation start.
The first measurement after irrigation (6–19 min after irrigation stopped) showed a mean deficit of 54.7 %, indicating that on average 31.2 % (between 18.6 and 43.9 %) of the water that has been recorded at the last measurements before irrigation stop was freely percolating and had left the monitored depth immediately. After this fast instantaneous reaction, the water content decreased equably. Mean total mass recovery dropped to 8.9 % after 18:24 h after irrigation start and almost returned to initial conditions (1.6 %) after 24:00 h after irrigation start.
The high variability in soil moisture dynamics observed in the TDR profiles
is summarized in Fig.
Soil moisture in the top 0.4 m of the soil of TDR1, TDR7, and TDR8 quickly
stabilized around constant values, indicating the establishment of quasi
steady-state conditions. After the end of the irrigation, the soil moisture
quickly declined down to a
The soil moisture patterns at the downhill monitoring area were more diverse.
Profiles located directly below the rain shield (TDR9, TDR3, and TDR10 with a
distance to core area of 0.2–0.5 m, Fig.
The TDR measurements at the downhill monitoring area were complemented by the
2-D time-lapse GPR measurements (see Fig.
Structural similarity attributes calculated from time-lapse GPR data. All measurements were referenced to the last one 24:00 h after irrigation start, indicating changes in the GPR reflection patterns associated with soil moisture changes. A structural similarity attribute value of 1 indicates full similarity; lower values signify higher deviation from the reference state. Water from the preceding natural rain event (green) was identified by constant or increasing structural similarity attributes. Water from the experimental irrigation (blue) was identified by decreasing values after irrigation start by more than 0.15. Within one column the rows give a sequence over time (after irrigation start). Columns proceed downhill, with increasing distance from the rain shield.
In transect 2 some weak signals appeared at the depth below 2.5 m 1:30 h after irrigation start. At this time, the signal was close to the noise level, but the pattern became stronger and more distinct in the following measurements. At transect 3, the persisting signal of the natural rain event made it difficult to identify the irrigation-induced response. However, a weak irrigation signal appeared after 1:28 h and reached its maximum at 6:45 h after irrigation start. At transect 4 the structural similarity attribute values were generally low, which indicates a low deviation from the reference state. Either the mobile water showed low dynamics (with regard to total mass over time) or water was less confined to specific structures and local changes are less pronounced. Both interpretations suggest that this transect was generally wetter due to its proximity to the river. Overall, the experiment does not appear to have affected this transect much.
Stable isotope data from precipitation, irrigation, piezometers, and
pore water samples.
The overview of all GPR measurements in Figs.
The temporal dynamics of the stable isotope compositions of the pore water
(selected depths shown as circles in Fig.
Only a few mL of water were seeping into the piezometers, with piezometer B
being the only one that could be sampled more than once. Piezometer B was
sampled first shortly after the irrigation ended (0:20 h) and showed a
composition that was close to the irrigation water. The other two samples
1:32 and 13:38 h after irrigation ended showed a decrease in
Piezometers A, C, G, and H were sampled once 13:38 h after irrigation ended. The water sampled from piezometers at the core area (A and C, pink diamonds) showed the same composition as the irrigation water. Piezometers located at the downhill monitoring area (G and H, purple diamonds) in contrast showed an isotopic composition similar to the rainfall water and different to the pore water in the depth profiles.
Top: depth distributions of response velocities calculated for the four time-lapse GPR transects. The blue scale indicates the response velocity calculated from the time of first arrival for each pixel. White areas did not show any irrigation water signal. The left plot shows the 2-D results for GPR transect 1. The margin plots on the right show the same data accumulated to 1-D depth profiles for all four GPR transects. Bottom: response velocities calculated from TDR measurements at the core area (strictly vertical), and the downhill monitoring area (vertical and lateral). The three plots showing the TDR profiles at the downhill monitoring area are sorted according to the three diverging transects. Lines within the right margins of each TDR plot show the installation depths of the TDR profiles. Grey sections indicate depth increments that did not show a change in soil moisture. Additionally, GPR-based velocities derived from 0.5 m wide sections of the GPR transects close to the TDR profiles are shown.
The results of the calculated response velocities from TDR and GPR
measurements are summarized in Fig.
At the core area, the dominating vertical response velocity was around
Similar to the vertical response velocities, the dominant TDR-based response
velocity at the downhill monitoring area was on the order of magnitude of
The GPR-based response velocities were calculated for the entire width of the
GPR transects down to the maximum depth of approximately 4.2 m
(Fig.
Areal share of activated regions per depth for the
natural rainfall event and the irrigation. Areal share of activated regions
for the natural rain event were calculated from the first measurement only
(also depicted in Fig.
The signal of the natural rainfall event could be observed throughout the
entire transects. The highest signal density (i.e., areal share) was found
between 0.9 and 1.7 m depth in all transects
(Fig.
The areal share of the irrigation signal was highest in transect 1, with
30.5 %, and decreased downhill, with 20.8 % in transect 2,
16.4 % in transect 3, and 6.0 % in transect 4
(Fig.
The natural rain signal in the GPR data was overpowered by the irrigation signal at 20:27 h, which is 3:23 h after irrigation start and about 22:45 h after the natural rain event. The dampened dynamics in transect 4 were due to its proximity to the river and therefore generally wetter conditions and less capacity for additional wetting.
Overview of sub-catchment size and accumulated specific discharge as a percentage of the precipitation amount (%).
The comparison of the two different response patterns shows that both the natural rain event and the irrigation caused advective flow in discrete flow paths more or less evenly distributed over the hillslope cross section. An (ephemeral) groundwater body or specific flow layers could not be identified in the top 4.2 m of the subsurface. Furthermore, the artificial irrigation had only a minor impact in comparison to the natural rain event, despite higher local input. Water that was supplied from upslope areas was therefore more important for the downhill soil moisture response than irrigation intensity or duration.
The mass balance at the core area showed an overshoot in calculated mass
recovery (i.e., higher mass recovery than water input) during the first
1:00 h of the irrigation period (Fig.
The fast soil moisture response in depth and at the downhill monitoring area
(Fig.
Various studies report a concentration of lateral preferential flow at a more
or less impermeable bedrock interface for other sites
The heterogeneous flow patterns observed with both TDR and GPR
(Figs.
The pore water and piezometer stable isotope composition at the core area
showed that the freely percolating water on the core area was predominantly
constituted of irrigation water (Fig.
The piezometers at the downhill monitoring area in contrast had water with
the same isotopic composition as rain water of the second rainfall event
prior to the irrigation experiment (Fig.
The subsurface response patterns revealed by the GPR measurements after the
natural rainfall events were similar to the irrigation-induced patterns with
regard to their patchiness, but showed a slightly different spatial
distribution (Fig.
The TDR measurements also showed high initial soil moisture content and a
strong reaction to irrigation at this depth. However, except for the slight
decrease in soil water content in the most downhill located TDR profiles
TDR6, TDR13, and TDR14 (Fig.
The timing of the response dynamics observed with the GPR measurements and
the discharge response also shed light on the prevalent processes. The
natural rainfall events ended at 21:35 h on 20 June 2013. The first GPR
measurements were taken at 10:42 h on 21 June 12:52 h later
(Fig.
At the time of the first GPR measurements, the first peak of the hydrograph
was already gone, while the second peak was on its rising limb and reached
its maximum 12:00 h later (24:52 h after the rainfall event,
Fig.
Several studies investigated the double-peak hydrographs of the Weierbach
catchment.
The stable isotope data collected during the rainfall event prior to the
irrigation experiment showed the same dynamics as observed by
Comparison of the GPR data of the natural rainfall event and the irrigation
reveals that the response in the shallow subsurface was stronger after the
natural event, even though the input per square meter was much lower than
during the irrigation (Figs.
In combination with this finding, the high potential response velocities
(Fig.
Preferential flow paths were established quickly, and high response
velocities have the potential to route water from the hillslopes towards the
river within a few hours. The presence of preferential flow paths and the
steep slopes in the Colpach River catchment were reported to enable
subsurface runoff, even at times when the soil and weathered zone are not yet
at field capacity
Many catchments reportedly showing double-peak hydrographs are headwater
catchments with predominantly steep slopes and shallow soils, and in many
cases with periglacial slope deposits
The processes causing the second peak could not be resolved with this study,
but it is hypothesized that deep percolating water from hillslopes and
plateaus caused the delayed response. This hypothesis is backed by a study
comparing catchments of different geology
Similar to the categorization of methods and observation data (see
Figs.
As elaborated in Sect.
In addition to pure response observations, however, basic knowledge about structures and local characteristics strongly improved the interpretability of our data and reduced the ambiguity. This basic knowledge included the presence of periglacial slope deposits, the downslope position at the hillslope, and the hydraulic conductivity of the subsurface. This information was easily obtained from the literature and in the field. It allowed us to close gaps in observational scales and link local observations at the hillslope to the overall system responses, and was thus the basis for more reliably relating the hillslope-centered and stream-centered observations.
Without this structural knowledge, the informative scope of response observations is limited to their observation scale. Transfer to other scales remains speculative. This fact is an important aspect, as most in situ response observations suffer from limitations in spatial resolution. Soil moisture measurements are restricted by their integration volume, and point measurements in general struggle to cover the entire domain. Here, more detailed information on (flow-relevant) structures might greatly improve our process understanding.
While we were able to describe processes in the investigated hillslope in
great detail, new findings on structure inferred from function observations
are scarce. Any details on the form of the investigated hillslope we
concluded from our observations were mere confirmations of previous
knowledge. The only knowledge on form that was gained from the presented data
concerns the flow relevance of structures. We found that substantial lateral
flow occurred at an intermediate depth, most likely associated with the
periglacial slope deposits. We also found that distinct preferential flow
paths occurred at greater depth, which suggests that the bedrock might not be
as impermeable as previously assumed
A conclusive picture of subsurface structures could not be drawn from process observations, partially refuting hypothesis H2, stating that function helps to reveal form. However, the observed response patterns were helpful in characterizing known structures with regard to their flow relevance.
The interpretation of the time-lapse 2-D GPR measurements is difficult and requires a thorough understanding of the expressiveness of the recorded data. While changes in structural similarity at a short timescale can be attributed to variations in soil moisture content, these changes contain no information on where the soil moisture content increases or decreases (i.e., the direction of the change). The data are qualitative information only, and supportive measurements are necessary. Therefore, GPR measurements need to be accompanied by other methods, such as TDR measurements or trenches, to provide a reference for the observed changes.
In the correct setup, however, 2-D time-lapse GPR measurements are a very
powerful tool and a valuable source of information. Especially in highly
heterogeneous hillslopes, the spatial context provided by the GPR
measurements is crucial for the investigation of complex preferential flow
networks. This spatial context can not be provided by ERT measurements with
their comparably low spatial resolution, highly invasive excavated trenches,
or by point measurements. In contrast to dye tracer excavations, time-lapse
GPR measurements yield the temporal component, which is necessary to cover
the highly dynamic processes. They allow for repetitions in time and space
and avoid the manipulating effect of a trench face on flow through the
unsaturated zone
Within the form and function framework, the biggest advantage of 2-D time-lapse GPR measurements lies in the combination of high-resolution spatial response patterns and dynamics. The method provides a direct link between flow-relevant structures and processes. It allows us to map response patterns in high temporal resolution, without manipulating the subsurface flow field. As such, this method has the potential to visualize the gradual establishment of flow paths, localize them, and calculate response velocities (hypothesis H3).
The study site is an example of headwater catchments with steep slopes and
young and highly structured soils, typical of landscapes that formed under
periglacial conditions. Here, preferential flow paths quickly developed in
the unsaturated zone within minutes after the onset of an intense irrigation
or rain event, causing lateral flow across the hillslope. In combination with
the high response velocities of up to
The strong dynamics and high spatial variability of preferential flow challenge the investigation of these processes. While we were able to describe the overall flow dynamics, the spatio-temporal resolution of our monitoring setup was not sufficient to reliably quantify the maximum response velocities. Our study has furthermore shown that causes and importance of observations can only be evaluated if the necessary context is known. This context includes knowledge of the spatio-temporal patterns on the one hand, and relevant process scales on the other.
The spatio-temporal context is provided by a combination of quantitative point measurements (TDR), qualitative mapping of patterns and dynamics (2-D time-lapse GPR), and the observation of integrated system response (hydrographs and stable isotopes). Either of these approaches provides a substantial piece to the puzzle, while neither of them on its own would have provided the full picture. The experiment has shown that time-lapse GPR measurements are a powerful tool which provides new perspectives for the investigation of preferential flow processes in hillslopes. The methodology's flexibility and minimally invasive character allow for repetitions in time and space, and, thus, the direct observation of processes under driven conditions. Depending on the research question, the method can replace labor-intensive trenches and increase the observation density.
The observation of response patterns and dynamics by means of the TDR and GPR measurements was shown to suffice to characterize subsurface flow within the hillslope. Processes were identified and characterized without any concrete information about spatial structures. However, despite the high number of TDR observations and the 2-D response patterns obtained from the time-lapse GPR measurements, our observations were methodologically limited in spatial and temporal resolution. Measuring intervals and integration volumes of the methods are restricted, and interpretations beyond observation scale remain speculative. Conclusions on or links to larger or smaller scales are not reliable. Here, more detailed information on spatial structures and their impact on flow processes might improve our understanding of the investigated area and will improve the ability to transfer findings to other scales by providing the physical basis behind the observed processes.
The observed response patterns, revealed by the GPR and TDR measurements,
allowed us to develop a conceptual description of the flow path network,
which is linked to subsurface structures. Certain spatial characteristics of
the flow path network such as layers prone to preferential flow could be
inferred from the response patterns. However, actual structural features,
such as the delineation of the deposit layer or the bedrock interface, could
not be localized. All structure-related conclusions merely confirm previous
findings. The topic of structural exploration is taken up in the companion
paper by
All data used in this study are foreseen to be published in Earth System Science Data (ESSD) as a concise outcome of the research project. Until then they are available from the authors on request.
The authors declare that they have no conflict of interest.
We are grateful to Marcel Delock, Lisei Köhn, and Marvin Reich for their support during fieldwork, as well as Markus Morgner and Jean Francois Iffly for technical support, Britta Kattenstroth for hydrometeorological data acquisition and isotope sampling, and Barbara Herbstritt and Begoña Lorente Sistiaga for laboratory work. Laurent Pfister and Jean-Francois Iffly from the Luxembourg Institute of Science and Technology (LIST) are acknowledged for organizing the permissions for the experiments and providing discharge data for Weierbach 1 and Colpach. We also want to thank Frauke K. Barthold and the two anonymous reviewers, whose thorough remarks greatly helped to improve the manuscript. This study is part of DFG-funded CAOS project “From Catchments as Organised Systems to Models based on Dynamic Functional Units” (FOR 1598). The article processing charges for this open-access publication were covered by a Research Centre of the Helmholtz Association. Edited by: Ross Woods Reviewed by: Frauke K. Barthold and two anonymous referees