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∘, excluding the plateaus. The plot had a slope of ∼ 14∘. While vegetation at the hillsope is dominated by beech forest (fagus sylvatica) of mixed age, the irrigation plot is placed in an area with no major trees. Except for a few young trees with breast height diameters below 0.1 m in the downhill monitoring area, all shrubs were cut to facilitate GPR measurements and allow for uniform irrigation. The entire investigated hillslope section covers an area of approximately 260 m2.

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 sprinklers had a nominated sprinkler radius of 4 m and were installed approximately 0.7 m (two uphill sprinklers) and 1.5 m (two downhill sprinklers) above ground surface. The level difference between the uphill and downhill sprinklers was 0.5 m. The 25 m2 area spanned by the four sprinklers is referred to as the core area, with a homogeneous irrigation intensity of ∼ 30.8 mm h-1 over 4:35 h. Total water input at the core area was 141 mm. These settings aimed at activating all potential flow paths and were chosen on the basis of an a priori simulation of the experiment see the Appendix of. Transferring this amount of water from the irrigated core area (5 m hillslope parallel length) to the entire hillslope uphill of the rain shield (219 m), this intensity compares to a rain event of 3.2 mm precipitation. While these irrigation settings do not mimic natural conditions, this relation allows us to compare and evaluate observations under experimental and natural conditions regarding lateral subsurface flow.

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 ∼ 120 m2.

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-1 and ended 29:33 h before the irrigation experiment; the second rainfall event had a mean intensity of 9.0 mm h-1 and ended 19:22 h before the experiment.

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. b). This setup allows for the separate observation of predominantly vertical flow at the core area and lateral flow processes at the downhill monitoring area.

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 ∼ 0.72 and 1.05 L, respectively. The manual measurements were conducted in 0.1 m depth increments and followed a flexible measuring routine with regard to the sequence in which the access tubes were measured. Thus, active profiles were covered with higher frequency.

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 ∼ 2, 3, 5, and 7 m to the lower boundary of the core area and were arranged approximately perpendicularly to the topographic gradient. Each transect was measured nine times. One measurement was taken before irrigation started and the last one about 24:00 h after irrigation start.

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 . To guarantee the repeatability of the 2-D time-lapse GPR measurements, all four transects were defined by wooden guides for an exact repositioning of the antennas. The measurement of one transect took approximately 2 min and measurements of all four transects were taken every 40–120 min during and after irrigation as well as 18:00 and 24:00 h after irrigation start.

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 (δ18O and δ2H) of the pore water. Two profiles were taken before the rainfall events, one after the first minor rain event on 20 June, and two more after the irrigation experiment (at the core area and the downhill monitoring area). All profiles covered a depth of ∼ 1.7 m below ground.

At the locations of the pre-irrigation soil cores, piezometers were installed. Additionally, three more piezometers were installed at a depth of ∼ 1.0 m. This depth was chosen based on observations in the core samples, which showed wet areas at the depths between 0.8 and 1.2 m, right above the Cv horizon. All piezometers consist of PVC tubes of 5 cm diameter and were screened at the bottom 20 cm. They were equipped with pressure transducers (CTD sensors, Decagon Devices Inc.). As only a few mL of water were seeping into the piezometers, water tables could not be properly monitored, and the data will not be shown. However, the water could be sampled using a peristaltic pump. In addition to the pore water and piezometer samples, bulk samples of rainfall water were collected during the rainfall events prior to the irrigation experiment and directly next to the irrigation plot. Water samples were also taken from the irrigation water reservoir five times during irrigation.

The soil samples were prepared following the direct equilibration method as proposed by and described in detail by . The precision for the method is reported to be 0.31 ‰ for δ18O and 1.16 ‰ for δ2H . All water samples were analyzed following the same procedure as described in Sect. .

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 , inverse distance interpolation between two locations is generally not appropriate. In the case of the vertical profiles, however, the integration depths of the probes exceeded the measuring increments. Due to the resulting overlap of the integration volumes, this procedure was assumed to be adequate. The measurement of one depth increment took between approximately 10 and 30 s. While the data were interpolated in time for better visualization, all data analyses were performed with the uninterpolated data.

All TDR measurements were referenced to the last measurement before irrigation. The resulting data set of relative soil moisture changes Δθ was used for the discussion of soil moisture dynamics and response velocity calculation (Sect. ). The storage changes (mm) in the top 1.4 m of the core area were estimated based on the four core area TDR profiles TDR1, TDR2, TDR7, and TDR8, by multiplying the Δθ (%) of each depth increment by the respective depth interval (mm). Together with the time series of water input, these data were used to estimate the mass balance dynamics of the core area.

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 . The GPR data were analyzed using an appropriate constant velocity and gridded to a 2-D transect with a regular trace-spacing of 0.02 m.

There is no standard interpretation procedure for the analysis of time-lapse GPR data. Most approaches are based on calculating trace-to-trace differences or picking and comparing selected reflection events in the individual time-lapse transects . In the context of this study, however, both approaches provided only limited interpretable information. Considering the methodological uncertainty, the highly heterogeneous soil did not provide reflectors which were a suitable reference. Therefore, we used a time-lapse structural similarity attribute presented by , which is based on the structural similarity index known from image processing . This approach incorporates a correlation-based attribute for highlighting differences between individual GPR transects and has been shown to improve imaging, especially for noise data and limited survey repeatability.

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-1. This velocity is based on additional common midpoint data and the assumption of static conditions during the experiment. Using this velocity, the GPR transects covered a TWT of 120 ns, which corresponds to a depth of ∼ 4.2 m below ground surface. Approximately the first 20 ns of each transect are influenced by the interfering arrival of the direct wave and the ground wave. Consequently, we observe no interpretable reflected energy in the uppermost time window. Thus, the 2-D GPR measurements imaged the subsurface between ∼ 0.7 and 4.2 m depth below ground.

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 t0, which was 15 min after irrigation start. Due to the slope-parallel or horizontal orientation of the saprolite, we assumed that the water flows either vertically or laterally rather than diagonally. Based on this assumption, the distances were calculated from the slope parallel distance of each profile from the lower boundary of the core area plus the depth of every measuring point. The distance assumptions for both, vertical and lateral velocity calculations, do not resolve tortuosity of flow paths and, therefore, drastically reduce the complexity of the flow path network to its integral behavior. The calculated response velocities are thus not to be interpreted as in situ flow velocities in the flow paths, but rather as the minimum necessary velocity explaining the observed arrival of the wetting signal.

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 . Here, we therefore simplified the 2-D patterns to a depth distribution of occurring response velocities. To do so, all areas that were newly activated at the time of one measurement were accumulated by depth and given as a portion of the entire width of each GPR transect. Comparable to the procedure applied to the TDR data, the response velocities were then calculated from the respective measuring time, the distance between transect and irrigation area, and the depth. The resulting patterns show the spatial fraction of the depth increment which is connected to flow paths of the calculated velocity or faster and give an idea of the spatial distribution of the GPR response velocities.

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. ). In the headwater catchments (Holtz 2, Weierbach 1 and 2), the first peak occurred almost instantly, while the more distant Colpach gauge showed a delay of approximately 3:00 h. The second response was prolonged, with a maximum approximately 36:00 h after the event. The strength and ratio of the two peaks varied across different sub-catchments and according to hydrological conditions, but the general pattern is characteristic of the hydrological behavior of the Colpach River catchment. Similar behavior was also reported by , , and , whose investigations focused on the Weierbach 1 catchment.

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 ). In the neighboring Weierbach catchment and the Colpach, the first peak contributed more strongly to the total event runoff (14.2 and 12.9 % at Weierbach 1 and 2, and 19.7 % at Colpach, Table ).

The δ18O signature of the stream water is indicative of the origin of the water. It showed strong dynamics during the discharge response to the rain events on 20 June (Fig. ). The results of the hydrograph separation show that the event water contributed up to 67.6 % to the event runoff during the response to the first rain event in the morning of 20 June (Colpach, 6:00 h). After that, the total discharge dropped again, with the event water contribution decreasing to 31.6 %. With the onset of the first peak caused by the second rain event at 19:20 h, the event water contribution increased again and reached values of over 50 % (58.0 % in the Colpach at 22:00 h, 55.2 % in the Holtz 1 catchment, 21:51 h on 20 June; Fig. ). δ18O values then declined, indicating event water contributions of around 20.0 % (24.8 % at 4:00 h in the Colpach, 18.1 % at 13:03 h in Holtz 2, and 16.2 % at 21:28 h in Holtz 1 on 21 June). Weierbach 1 and 2 showed the same pattern, with event water contributions well above 50.0 % for the first peak of the second rainfall event.

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. a). The subsequent GPR measurements furthermore show the temporal dynamics of the rainfall signal, overlain by the irrigation signal. The high initial signals, as well as the high but decreasing areal share of active regions in all transects during the first measurements until 1:30 h after irrigation start (Fig. b), indicated free water remaining from the preceding natural rain event which slowly disappeared.

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. b).

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 ± 73 mm h-1, with slightly higher values in the vicinity of the four sprinklers. Surface runoff at the lower boundary of the core area started 20 min after irrigation start and ceased with the same time lag. In total, surface runoff amounted to 0.5 L, which equals only 0.02 % of the water balance.

The core area mass balance is shown in Fig. , depicting the storage increase in the top 1.4 m of the soil. All profiles showed a mass recovery of more than 100 % (i.e., higher storage increase than water input at measuring time; see Fig. ) in the first 60 min of the irrigation period. In profiles TDR1, TDR2, and TDR8 mass recovery then decreased and dropped below 100 %, while TDR7 increased further, with a maximum overshoot of almost 50 % approximately 2:00 h after irrigation start. The last measurement during irrigation was taken approximately 50 min before the end of the irrigation period. At this time, the average storage increase was more than 20 % lower than the input mass.

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. . The four uppermost panels (rows 1 and 2) show the core area profiles. Columns represent the three diverging TDR transects. The general pattern observed at the core area was characterized by a strong and comparably fast response in the top 0.4 m of the soil and below the depths of approximately 1.2 m. The response in between these active layers was more diverse and generally weaker.

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 Δθ of 4 % vol, indicating a very fast response to the dynamics of the water input. In contrast to the fast establishment of steady-state conditions and the fast decline, a slightly increased water content of up to 4 % vol above initial conditions was persistent in distinct depth increments and was also measured even 24:00 h after irrigation stopped.

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. ) exhibited dynamics that resemble the reaction at the core area, but with mostly lower intensities and higher variability in depth. More distant TDR profiles however showed a highly variable picture. Distinct layers in variable depths were activated, while no change in the water content was seen at the other soil depths. Especially noteworthy are TDR10 and TDR11, which showed a strong soil moisture increase of up to 18 % vol below 1.4 m depth and around 10 % vol in the top 0.3 m of the soil. Profiles TDR13, TDR6, and TDR14 showed only weak signals, with the strongest response below 1.4 m below ground in TDR6. Profiles TDR6, TDR12, TDR13, and TDR14 showed the strongest decrease in soil moisture over the course of the measurements, with Δθ of -3.7, -4.4, -5.8, and -6.2 % vol at certain depths, indicating vanishing free water from the storm event. While the results from the left (TDR7, TDR9, and TDR11) and right (TDR8, TDR10, and TDR12; see Fig. ) transects suggested lateral flow at different depths, the central transect (TDR1 through TDR6) did not indicate lateral flow.

The TDR measurements at the downhill monitoring area were complemented by the 2-D time-lapse GPR measurements (see Fig. ), yielding 2-D images of structural similarity attributes referenced to the last measurement 24:00 h after irrigation start (Fig. ). The first irrigation signals (shown in blue in Fig. ) appeared in the first measurement after irrigation start (1:28 h), with transect 1 showing the clearest response. After about 3:23 h strong, localized signals occurred and increased in intensity over time. The general maximum was reached approximately 5:18 h after irrigation start, showing distinct activated flow paths. Most signals started to decline after 6:45 h, which is 2:10 h after the end of the irrigation period.

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.

The overview of all GPR measurements in Figs. b and  visualizes the dynamics of the hillslope section. The green natural rainfall signal faded from uphill to downhill, with the highest intensity and duration in transect 3. After irrigation start, the blue irrigation signal appeared, gradually propagating downhill and eventually overpowering the natural rain signal; 18:00 h after irrigation start (i.e., 13:25 h after irrigation ended), no changes in the GPR signal could be observed anymore. This suggests steady soil moisture conditions and, thus, the absence of highly mobile water in all transects. The mobile water either left the monitored area or dispersed by diffusion into the matrix surrounding preferential flow paths, where it remained beyond the time of the reference measurement and thus would not have been visible by means of structural similarity attributes.

The temporal dynamics of the stable isotope compositions of the pore water (selected depths shown as circles in Fig. a) partially traced the signals of the rainfall and irrigation water input (green lines and blue triangles). The high δ2H signal of the first minor rainfall event (dark green) was clearly visible in the top 10 cm below ground in the profile sampled at the downhill monitoring area 24:00 h before irrigation and 5:30 h after this rainfall event (Fig. a and c). Similarly, the isotope signal of the second rainfall event (light green) and the irrigation water (blue triangles) could be seen in the top 10 cm of the soil at the core area and the downhill monitoring area, respectively. Especially the isotope profile taken at the core area after irrigation showed an increase in δ2H in the top 0.85 m below ground, showing the influence of both, the irrigation and the event water. Below the depth of approximately 1.2 m of all profiles, the soil water isotope composition seemed not to be impacted by the rainfall events and irrigation.

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 δ2H, towards the composition of the soil water (red and orange diamonds in Fig. ).

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.

The results of the calculated response velocities from TDR and GPR measurements are summarized in Fig. . The top row shows the depth distribution of observed response velocities for all GPR transects. The bottom row shows the TDR-based results, separated into core area profiles and the three diverging transects. In addition to the TDR-based response velocities, GPR-based velocities observed in 0.5 m wide sections of the GPR transects which were closest to the displayed TDR profiles are shown in the plot.

At the core area, the dominating vertical response velocity was around 10-4 m s-1, with a tendency to increasing velocities with depth (Fig. , bottom left). As response velocities were calculated for the entire soil profile above the measuring depth, this increase indicates a bypass of intermediate depths through preferential flow paths, and a limited and slow interaction with the matrix. The highest observed vertical velocity was 10-3 m s-1 at the depth of 1.4 m below ground. The respective soil moisture signal was recorded in the very first measurement after irrigation start, which indicates that we might have even missed the first response.

Similar to the vertical response velocities, the dominant TDR-based response velocity at the downhill monitoring area was on the order of magnitude of 10-4 m s-1 (Fig. , bottom row). Response velocities of around 10-3 m s-1 were observed in six profiles all over the downhill monitoring area, of which the highest values (1.0 to 1.6×10-3 m s-1, TDR4, TDR6, TDR11, and TDR17) are based on signals observed during the first profile measurements after irrigation start. The fastest response was observed in the top 0.5 m (TDR4, TDR6, and TDR10) of the soil and below a depth of 1 m (TDR6, TDR11, TDR17, and TDR18).

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. , top), and for single sections close to the TDR profiles down to a depth of 1.7 m for comparison of the methods (Fig. , bottom). All GPR transects showed slight and localized irrigation water signals in the data collected 1:28 h after irrigation start (see Fig. ). This translates to response velocities between 1.4×10-3 and 2.2×10-3 m s-1, depending on the distance to the irrigation area and signal depth. The data of the next measurements suggest response velocities between 5.4×10-4 and 8.2×10-4 m s-1. Given the fact that this is a conservative estimate due to the even sparser temporal resolution in comparison to the TDR measurements, response velocities are likely to be similar to or even higher than those calculated from TDR results.

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. ). This might have been related to the spatial heterogeneity in irrigation intensity or lateral redistribution of water in the shallow subsurface. After that, the four core area profiles behaved differently. While the storage change in TDR7 was continuous, the other three profiles showed a stepwise behavior with abrupt stagnation and storage increase. This behavior is interpreted as a stepwise activation of flow paths in the vertical or lateral direction. The decrease in mass recovery, which started approximately 1:00 h after irrigation start, signified a loss of water from the core area (0–1.4 m depth). Thus, flow paths towards greater depth and the downhill monitoring area were established around this time.

The fast soil moisture response in depth and at the downhill monitoring area (Fig. ), as well as the immediate drainage after irrigation stop according to the mass balance (Fig. ), also suggested a high fraction of mobile water. The mobile water is not bound to the matrix and is likely subject to advective flow with high velocities of over 10-3 m s-1, according to the first response observed in TDR and GPR measurements (Fig. ). The order of magnitude of the response velocities agreed with the in situ measurements of hydraulic conductivity (up to 10-3 m s-1 and higher), but clearly exceeded the potential of matrix flow for the silty matrix material . Similarly high preferential flow velocities are reported for the well-studied MaiMai hillslope, with initial breakthrough velocities between 6.7×10-3 and 3.3×10-2 m s-1, being at least 2 orders of magnitude higher than matrix flow, which ranges between 3.8×10-6 and 1.04×10-4 m s-1 .

Various studies report a concentration of lateral preferential flow at a more or less impermeable bedrock interface for other sites e.g.,, which has also been hypothesized for the Colpach River catchment e.g.,. However, none of the piezometers showed a significant reaction, despite being installed at the depths with the highest observed soil moisture responses. Instead, both TDR profiles and the time-lapse GPR transects revealed very heterogeneous patterns and a soil moisture response at multiple depths, as was also reported by for a mountainous hillslope with young, structured soils.

The heterogeneous flow patterns observed with both TDR and GPR (Figs.  and ) and the delayed signal at the intermediate depth at the core area (Fig. ) suggest a heterogeneous network of preferential flow paths which bypassed a large portion of the unsaturated soil see also. The water passes either through the intermediate depth outside of the monitored soil volume or through small preferential flow paths. If the volume of these flow paths is small in comparison with the soil volume monitored by the TDR probes, they will only become visible (by means of soil moisture changes) if the water leaks into the surrounding matrix and effectively increases the soil moisture content of the integration volume. While we can not distinguish between these processes by means of the data presented here, both are preferential flow processes acting at different scales.

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. a and b). Piezometer B, which was the only piezometer to be sampled more than once, showed a trend from irrigation water composition shortly after irrigation stop, towards pore water composition, 14:38 h later. This trend indicates that the irrigation water first percolated through the preferential flow paths without significant mixing with old water. After the water supply ended, however, preferential flow is (partially) fed by pore water, suggesting mixing and interaction between matrix and preferential flow as suggested by .

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. c). This water has been re-mobilized, as it only seeped into the piezometers after the irrigation, but shows no signs of interaction with the soil matrix or the irrigation water. While this observation has previously been made in other soils with well-developed macropore systems , it contradicts the observations at the core area and rather suggests dual flow domains.

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 GPR measurements 12:52 h after the second rain event showed the highest density of response signals at the depths between 0.8 and 1.7 m (Figs. a and ). The higher response in the shallow depth could be interpreted as the signal of vertically infiltrating rain water, which did not occur during the irrigation. This depth also correlated with high stone content and the periglacial cover beds, which are characteristic of the area e.g., and have also been observed at the investigated hillslope . While no (transient) water table could be detected at the monitored depth, the patterns indicated a concentration of preferential flow paths at this depth.

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. ), soil moisture values barely fell below the initial values measured between rainfall events and irrigation. This means that the signal of the natural rainfall events was already gone in the shallow subsurface, and that no information on the natural rain signal in this depth can be derived from the TDR data.

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. ). Located at the lower section of the hillslope, they were interpreted to show a declining soil moisture signal, which was mostly gone 37:22 h after the second rainfall event (i.e., 18:00 h after irrigation start; see Figs. b and ). Following the hypothesis of a top-to-bottom drainage of the hillslope, and considering the downslope location of the study site, the recorded signal represented the tailing of the shallow subsurface flow response to the natural rainfall event.

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. ). Thus, the following decline in subsurface response was observed after the first peak and coincided with the rise of the second peak. This timing provides strong evidence that the second hydrograph peak was not primarily caused by the activation of the observed preferential flow paths in the shallow subsurface.

Several studies investigated the double-peak hydrographs of the Weierbach catchment. used dissolved silica and electrical conductivity and found that the first peak was dominated by event water, while the second peak mainly consisted of pre-event water and strongly depended on antecedent conditions. Based on these observations, the first peak was attributed to fast overland flow from near-stream areas, while the second peak was attributed to subsurface flow where antecedent water was mobilized. came to a similar conclusion and identified a riparian zone reservoir as the origin of the first peak.

The stable isotope data collected during the rainfall event prior to the irrigation experiment showed the same dynamics as observed by (Fig. ). The isotopic composition of the first peak suggested a mixture of event water and pre-event water, while the composition of the second peak indicated the dominance of pre-event water. A simple water balance revealed that the total mass of the first peak of the event runoff accounted for about 4 % of the precipitation amount in the Holtz 2 catchment. Based on a rough delineation, the existing wetland patches in the catchment amounted to approximately 800 m2 in the source area. Thus, the specific discharge of the first peak exceeded the existing wetland patches or riparian zones of the headwater catchment by a factor of 27, and suggests that overland flow from near-stream saturated areas could not solely explain the observed discharge response.

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.  and ). The observed response could only be caused by the accumulated water input of the (entire) hillslope draining through the shallow subsurface. Thus, the hillslope is prone to a substantial amount of lateral flow, which quickly ceases after water supply stops.

In combination with this finding, the high potential response velocities (Fig. ) revealed by the TDR and GPR measurements show that fast, lateral subsurface flow is an important process in the investigated hillslope. The timing of the hydrograph dynamics and the declining response in the GPR measurements described above (Fig. ), as well as the freely percolating rainfall event and irrigation water shown by the stable isotope data, give further evidence that the activation of preferential flow paths within the shallow subsurface was contributing to the first immediate peak of the stream hydrograph.

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 . Such systems are characterized by pronounced subsurface structures and therefore are prone to heterogeneous flow patterns and preferential flow at the plot and hillslope scale. The results on subsurface structures presented in the companion study by also support this interpretation. Inter-aggregate flow paths at the scale of 5×10-3 to 5×10-2  m are the reason for the highly variable hydraulic conductivities found in the investigated area and enable such high flow velocities. While these structures could only be revealed at the plot scale by excavation and direct observation, the related patterns in soil moisture response were similar (with regard to activated depths and response velocities) also for lateral flow at the hillslope scale.

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 , where the prolonged response of double-peak hydrographs was identified as an indicator of deeply percolating subsurface flow through bedrock fissures. This theory might also apply to the catchment investigated here, with its fractured schist bedrock . Furthermore, deep subsurface storage overflow and fast groundwater displacement are processes which may play a role in the behavior of the Colpach River catchment. These hypotheses are also backed by the isotopic composition of the second peak, suggesting the dominance of pre-event water (Fig. ), and could explain the dependency of the occurrence of double-peak hydrographs on groundwater storage as described by and . They could only observe the second peak if the groundwater storage was sufficiently filled, resulting in a hysteretic threshold behavior for the occurrence of the second, delayed peak.