Interactive comment on “ Subsurface structures of a quick-clay sliding prone area revealed using land-river reflection seismic data and hydrogeological modelling

(A. Booth Referee #2) b) Sometimes the interpretation of the seismic data is also overlong, but also overinterpreted. I list some specific examples below (Points 13-16), but the key point is that not all of the seismic observations appear to have significance in the model – so I think you should restrict the discussion of the interpretation to the most relevant parameters. A full interpretation could go into supplementary material, although (see below) I’d suggest that some of this is over-interpreted anyway.

hazard assessment, (iii) hydrological modelling of the groundwater within the coarse-grained layer to better understand the development of quick clays in the study area, and (iv) investigating the riverbanks of the Göta River, its bed and massmovement deposits. Reflection seismic, P-wave refraction tomography (Wang et al., 2016), and resistivity models (Bastani et al., 2017;Wang et al., 2016) are correlated with borehole data (Branschens Geotekniska Arkiv-BGA, 2018;Salas-Romero et al., 2015) for the identification of different types of clays, coarse-grained materials and bedrock. Using the interpreted 5 seismic sections together with total sounding (BGA, 2018) and high-resolution LiDAR data (© Lantmäteriet), elevation surfaces from the top of bedrock and top and bottom of the coarse-grained layer are modelled. This study shows not only that this layer probably covers a larger area than initially thought (earlier studies showed the local extension of this layer), but also confirms its hydrological potential as a transport path for infiltrating fresh water from nearby outcrops and fractures.
Magnetic surface data serve for illustrating that the coarse-grained layer together with quick clays may have acted as sliding 10 surface at the landslide scar located within the survey area. Other surface data, such as side-scan sonar and bathymetry, are also analysed to investigate the riverbed and their influence on the development of quick-clay landslides. This work provides a good example of the integration of a large amount of different types of data for the study of an area prone to quick-clay landslides.
Marin Miljöanalys AB collected the bathymetric data using multi-beam echo sounding (Kongsberg EM3002-D, 300 kHz) in 2009 under the assignment of SGI (Marin Miljöanalys AB, 2009). The goal was to create a high-resolution topography model of the riverbed. The data were available as a georeferenced file (see resolution in Table 2).

LiDAR
The LiDAR scan was collected by Lantmäteriet in 2011. The survey was done from a height of 2000 m and the average 5 point density is from 0.5 to 1 points/m 2 (see resolution in Table 2). Table 3 presents the main processing steps for the land and river reflection seismic data. The processing of the land reflection seismic data was similar for lines 2-2b, 6 and 7. The preparation of the data required zero-time correction, vertical stacking of repeated shot records, as well as merging of the new line 2b with the 2011 line 2 (Malehmir et al., 2013b). 10

Reflection seismic processing
Removal of first arrivals using a carefully designed top mute filter using picked first breaks and the application of stretch mute (Schmelzbach et al., 2005) helped to enhance the reflections at the shallow parts and avoid misinterpretation of the first arrivals. Refraction static corrections did not give satisfactory results for any of the lines, and they were not applied further.
Elevation static corrections were, however, applied using the highest elevation as datum and a velocity of 1500 m/s. As the data still looked noisy and with lower resolution, more preprocessing steps were necessary. Deconvolution before stacking 15 helped in obtaining a reasonably clear seismic section. A series of constant velocity stacks (from 800 to 4000 m/s) was used in order to obtain the most coherent bedrock reflections. A post-stack fk-filter and surface-consistent residual static corrections were applied for data along lines 6 and 7 for improving the continuity of the reflections. Black et al. (1994) show that the migration process is not really necessary for near-surface seismic imaging applications although it can reduce the noise level. After a series of tests we eventually concluded that migration did not lead to any improvement because the 20 reflections are mostly subhorizontal or gently dipping. Figure 3 shows an example of a shot record from line 7 (SH7, see the position in Fig. 2a). Figure 3a presents the raw shot gather with only trace balance applied, and Fig. 3b presents the preprocessed shot gather after elevation static corrections, Wiener deconvolution, band-pass filter, trace editing, removal of first breaks and trace balance. The bedrock reflection, B1, is visible already in the raw data but improved in the preprocessed shot record. 25 The processing of the land reflection seismic data for line 5-5b was slightly different from the rest of the lines. First, the wireless data needed to be resampled from 1 to 0.5 ms to be consistent with the cabled geophone data. Then, the cabled geophone, 1C and 3C wireless (vertical component) data were merged. Once all the data were joined, a delay of around 1 s between the cabled geophone and the wireless part was observed (the wireless data were shifted up 1 s). With the data zerotime shifted, the next step was to merge them with those from the 2011 line 5 (Malehmir et al., 2013b). As the receiver 30 distance was different for the cabled geophone and the wireless parts, it was necessary to process each part separately, applying different geometries for each case (common depth point, CDP, spacing equal to 2 m in the south and 10 m in the north). Before velocity analysis, both processing included elevation static corrections, removal of first arrivals using a top mute filter (surgical mute for the wireless data), band-pass filter, spectral whitening, and fk-filter for the wireless data. The high-quality data for line 5-5b allowed a relatively simple processing flow, where the most important step was the velocity analysis (performed at 10-20 m lateral spacing in the southern part; in the northern part constant velocities, from 800 to 4000 5 m/s, were tested). The velocity analysis of the wireless seismic data revealed that the deeper part of the section needed higher velocities to obtain visually coherent reflections, thus the data were divided in two parts for processing: from 0 to 80 ms and from 80 to 500 ms. The post-stack processing included band-pass filter for both types of data (cabled geophone and wireless), and post-stack deconvolution in the case of the wireless data. Figure 4 shows an example of a shot record along line 5-5b (SH5, see the position in Fig. 2a). Figure 4a is the raw shot 10 gather, and Fig. 4b is the preprocessed shot gather (elevation static corrections, band-pass filter, spectral whitening, trace editing, removal of first breaks and automatic gain control, AGC). In Fig. 4b a number of reflections seem to be revealed; bedrock reflection B1 and a shallower one from a coarse-grained layer S1. The sediments show P-wave velocities ranging from 1000 to 2000 m/s, while bedrock shows velocities much higher than 3000 m/s (Wang et al., 2016). The values are similar to those in line 7 (Fig. 3a), except for the direct wave, which is much slower in that case. It may be related to near 15 surface effects or differences in topography.
The processing of the river reflection seismic data was simpler compared to the land seismic processing (Table 3). In the case of the single-channel data only Wiener deconvolution was applied for removing multiples as much as possible. The sixchannel data required the creation of marine geometry according to the receiver and shot positions. A CDP spacing of 1.5 m was used for making the geometry. For the six-channel data more processing steps were necessary, where Wiener and post-20 stack deconvolution helped to improve the final results.
Land and river reflection seismic data were time to depth converted using a constant velocity of 1500 m/s. This value was justified based on the available borehole data for depth calibration, although a slight error on the order of 1-3 m can still be expected.

Land seismic lines
Figure 5a-d shows, from top to bottom, the seismic results for line 2-2b, the interpreted horizons and structures, i.e. S1, B1 and F, and the P-wave refraction tomography and RMT resistivity results obtained in earlier studies (Wang et al., 2016).
Figure 5b also includes the natural gamma radiation and magnetic susceptibility data from borehole BH1 (Salas-Romero et al., 2015), and the total sounding data from borehole 7065 (BGA, 2018). S1 is a subhorizontal layer only identified in the 30 southeastern part of the line; the strong decrease in the gamma log of BH1 (distance to the seismic line 13.4 m) and the increase of the magnetic susceptibility coincide with this interface. S1 is a coarse-grained layer previously identified in  -Romero et al. (2015). In the northwestern part of the line, next to the river, the S1 reflection is not visible. B1, interpreted as the top of bedrock (BH1 reached the top of bedrock, see Salas-Romero et al., 2015), is more irregular and has a higher amplitude reflection than S1. B1 shows a clear undulating morphology, reaching the ground surface at approximately CDP 525, and dipping towards the river in the northwestern side; in borehole 7065 (distance to the seismic line 0.02 m) the strong increase in the total sounding curve happens at bedrock depth, not showing any important change at 5 the suspected position of S1. The discontinuous reflectivity at bedrock level indicates the presence of fractured or disturbed materials (F) in the northwestern side. The P-wave refraction tomography results (Fig. 5c) indicate, in general, high velocities (>4000 m/s) below B1 and lower velocities in the overlying sediments (mostly between 350 and 3000 m/s). The top of bedrock is well delineated by high velocities with some exceptions at the extremes of the line, which may be due to the lack of ray coverage. The S1 horizon shows for the most part higher velocities (1500-3000 m/s) compared to the 10 sediments above and below this layer in the southeastern part of the line. The resistivity results only cover part of the line ( Fig. 5d); above the thin dashed white line, the RMT model is well resolved with high confidence. Wang et al. (2016) estimated the penetration depth (thin dashed white line position) using a method shown by Spies (1989), and the same criterion is followed for the rest of the lines. Low resistivity values (between 3 and 100 Ωm) are observed above B1, and higher values (>100 Ωm) below, with very high at the position closer to the surface (up to 1000 Ωm, some outcrops are close 15 to this location, see Fig. 2b). At the S1 position the values are around 80-100 Ωm, which agrees with the material classification (coarse sediment) given in Solberg et al. (2012). The values immediately above S1, between 10 and 80 Ωm, may indicate silt or leached clay deposits-potential quick clays (Solberg et al., 2012). Quick clay was identified above the coarse-grained layer during the visual inspections of the core samples of boreholes BH1 to BH3 (Salas-Romero et al., 2015). Figure 6a-e shows the seismic results for line 5-5b, their interpretation, the earlier P-wave refraction tomography and RMT 20 resistivity results (Wang et al., 2016), and the airborne transient electromagnetic (ATEM) resistivity results (Bastani et al., 2017). Figure 6b also includes the natural gamma radiation and magnetic susceptibility data from borehole BH3 (Salas-Romero et al., 2015), and the total sounding data from borehole 7062 (BGA, 2018). Note that the quality of the seismic data is different on each side of the river, due to the lower sampling in the northern side (10 m). Nevertheless, the delineation of S1 and B1 is possible along the whole line. The S1 horizon shows continuity along the line, except between CDPs 400 and 25 480. At these positions S1 is not visible, likely due to lower fold in the seismic data (see fold distribution along line 5-5b in Fig. 6a). Other possibilities cannot be disregarded, e.g. bedrock movement and/or fractures in the bedrock, and/or deposits disturbed by human activities such as excavation works (a trench runs perpendicular to the line at this position, although neither its width nor its depth seem to be of the same size of the observed anomaly in the seismic data). A fracture (F) can be inferred in the bedrock at around CDP 440 with some diffraction signatures suggesting the presence of a strong bedrock 30 curvature or edge. The biggest changes in the gamma and magnetic susceptibility logs in BH3 (distance to the seismic line 0.23 m) and in the total sounding curve in 7062 (distance to the seismic line 90.3 m) coincide with the depth of S1. The undulating B1 reaches close to the surface around CDP 500 and dips to the river after this point; no clear bedrock dipping is observed in the opposite northern shore data. Below the landslide scar displacement and oblique translation of some reflections are observed; the sediments appear to have slid towards the river. The top of bedrock at the river position may be at a depth of around 100 m. The P-wave refraction tomography results (Fig. 6c) in the southern side indicate, in general, high velocities (>3000 m/s) below B1 and lower velocities in the overlying sediments (between 300 and 1500 m/s). In the northern side of the line, the tomography results and reflection B1 agree in the northernmost part of the profile, with high velocities (>3000 m/s) below B1. From the river to CDP 1000 individual high-velocity anomalies (>4000 m/s) are visible 5 above B1, which may be related to the presence of boulders. The S1 horizon shows higher velocity than the sediments around it in the northern part of the line, which is similar to what is observed in Fig. 5c for line 2-2b. In contrast, the southern part of the line does not show any velocity difference at the S1 interface. The RMT resistivity values (Fig. 6d) are mostly high (>100 Ωm) below B1 although the northern side does not have data below the top of bedrock. Above B1, the RMT resistivity values are low (between 1 and 10 Ωm) except along the S1 horizon, where the values reach >100 Ωm. The 10 values immediately above S1 may indicate leached clay deposits-potential quick clays ( (Wang et al., 2016). In this case only B1 is identified in the seismic section. The bedrock shows undulating 20 morphology, dipping to the west towards the river, and reaches the ground surface at the end of the line in the eastern side.

Salas
Between CDPs 100 and 200 from -50 to -100 m elevation (Fig. 7b), a different reflection pattern (dipping to the east of the line) is present, which may be related to 3D effects caused by the rough bedrock topography. Fractured or disturbed materials (F) are identified in the western side of the line and also at around CDP 260. The F materials located closer to the river seem to coincide with a probable fracture zone present in Fig. 2a, which runs parallel to the river profile. The velocities 25 ( Fig. 7c) are, in general, high (>3000 m/s) below the B1 reflector, except between CDPs 150 and 200 where the velocity is high (>3000 m/s) above B1.  (Wang et al., 2016). Figure 8b also includes the total sounding data from boreholes 7073 and 7075 (BGA, 2018). B1 is delineated along the line, having the similar appearance as in line 6 ( Fig. 7b). The S1 30 reflection is only delineated between CDPs 100 and 210. Boreholes 7073 and 7075 (distance to the seismic line 29.3 and 1.6 m, respectively) located in the western side of the line show strong increases in their curves at the S1 interface. Some and low in the overlying sediments (approximately between 450 and 2000 m/s). In the western side of the line the ray coverage is poor at the depth of B1. The tomography results do not show any velocity difference at the S1 interface. The resistivity values are high (>100 Ωm) below B1 in the eastern side (Fig. 8d); the western side does not have resistivity results below B1 and only partial results above it. The resistivity values are around 10 to 100 Ωm at shallower depths, except at the S1 position and below it where the values are lower, between 1 and 10 Ωm. In terms of resistivity, these values do not 5 indicate coarse sediments but unleached marine clay deposits (Solberg et al., 2012). Nevertheless, the resistivity model is not well resolved below 10 to 30 m depth along the line. depressions can reach up to 10 m difference in height with respect to peaks or mounds that are found between them. Only a peak of the bedrock interface (B1) is interpreted between 5500 and 6000 m distance, separating two adjacent channels. The interpretation of the areas separating adjacent channels in the rest of the cases, at distances around 2800, 8000, 11500, 13000 and 15000 m, is complicated because no more structures are clearly visible. The reasons may include the bedrock being very close to the surface and/or the presence of fracture zones as shown in the interpretation of the six-channel data. 20

River seismic lines
The results of the six-channel data collection (© SGU) and their interpretation are presented in Fig. 10a and 10b, respectively. Figure 10b also includes the total sounding data from boreholes 11014, 11034 and 11094 (BGA, 2018). The difference in height between the valleys and peaks reaches up to 15 m (Fig. 10a). Although the resolution of the six-channel data compared to the single-channel data is lower, geological features can be distinguished at greater depth (>100 m). In the interpreted section (Fig. 10b) the same channels (C) identified in the single-channel data ( Fig. 9b) can also be delineated, as 25 well as the bedrock highs between 5500 and 6000 m distance (there is a difference of about 10 m in height between both data sets at this point, probably due to the distance between the lines). Strong variations in the borehole data coincide with the filled channel positions. The bedrock undulates and presents several fracture zones between CDPs 800 and 1000, 1350 and 1400, 2350 and 2500, and 2950 and 3000. These fracture zones coincide with fracture zones identified using the geological information provided by SGU (Fig. 2a). Along the whole line fractured or disturbed materials (F) can be identified at the 30 shallowest sediments, and also at bedrock level. In Fig. 10b we can also observe that the reflection amplitude decreases between CDPs 3000 and 5402, the deeper areas being more affected. The bedrock interface (B1) may be closer to the surface at these positions, thus the low-amplitude region would represent the transparent crystalline bedrock.  Figure 11 shows a detailed section of the river seismic data (© SGU) between CDPs 1800 and 3300. The portion of sidescan sonar data (© SGU) corresponding to the profile AA' (Fig. 11b-c) is presented in Fig. 11a. Figure 11b and 11c are the interpreted sections of single-and six-channel data. Line 5-5b crosses a fracture zone. In Fig. 11a hummocks and disturbed riverbed are observed at the centre of the river bottom; these may be interpreted as landslide debris. The shade colour and the texture indicate denser and coarser deposits, respectively, compared to their surrounding materials. At the position of line 5-5 5b, a landslide scar can be found in the southern side of the river (see also Fig. 2a and 6a). In the opposite riverbank two more landslide scars are found as well as one gully flowing from the south and a tributary flowing from the southeast ( Fig.   2a-b). Based on Fig. 11a, it is unclear whether the deposits at the river bottom originate from the landslides or are fluvial sediments.

Comparison with previous studies
Previous findings established that the formation of quick clays in the study area is influenced by the presence of underlying coarse-grained materials (Löfroth et al. 2011;Malehmir et al., 2013aMalehmir et al., , 2013bSalas-Romero et al., 2015;Wang et al., 2016).
The coarse-grained layer serves as a path for the leached substances to be transported towards the river. Salas-Romero et al.
(2015) mention that the presence of this layer expedites the development of quick clays: infiltration of surface water through 15 outcrops and fracture zones allows relatively fresh water to reach the glacial and postglacial sediments, which leads to leaching of salts and promoting quickness. The borehole information available in the area (BGA, 2018;Löfroth et al. 2011;Salas-Romero et al., 2015) can be used for determining the presence of potential quick clays, coarse-grained materials or top of bedrock.
Although the correlation between different geophysical data sets seems to work well (Fig. 5,6,7 and 8), this study shows 20 that the reflection seismic method allows higher resolution delineation of the bedrock surface and coarse-grained layer compared to the other methods. Electromagnetic methods (e.g. RMT) help to discriminate clay from sand deposits as well as leached from unleached clays (if the shallow clay layer is not too thick). Thus, they complement the reflection seismic data when studying areas prone to quick-clay landslides. Borehole data at the site (BGA, 2018) show that the coarse-grained layer can be found in many points to the north and south of the study area, although in some cases it is only a very thin layer (0.5 25 to 1 m). This wide extension is consistent with the reflection seismic results since the coarse-grained layer can be delineated in most of the lines (Fig. 5, 6, 8, see also Malehmir et al., 2013b).
Fractured or disturbed materials are identified in all the seismic lines. The six-channel river seismic data show several fracture zones. These fracture zones, as well as some of the fractured materials interpreted in the land seismic lines coincide with the position of morphological or geological lineaments (usually fracture zones) shown in the geological map (Fig. 2a). 30 Using complimentary geophysical methods helps interpreting these structures. For example in the case of line 5-5b (Fig. 6b cabled geophone and wireless data already indicated a possible fracture in the river. In comparison, ATEM resistivity results (Bastani et al. 2017;Malehmir et al., 2016) show a low resistivity zone at the river position (Fig. 6e), which is interpreted as a possible fault. A fracture zone is also identified in the six-channel river seismic data at the same position ( Fig. 10b and 11), as a zone of lost reflectivity. It is interesting to notice that the interpreted fracture system occurs where a quick-clay landslide scar is present. We interpret the combination of coarse-grained layer, bedrock morphology and presence of fractured bedrock 5 to contribute to the formation of quick clay and to be likely pre-conditioning factors for landslide (see e.g. L'Heureux et al., 2017).

3D Modelling of the subsurface materials
One of the main objectives of this study was to obtain the extension of the coarse-grained layer and its spatial relationship with the bedrock surface. Malehmir et al. (2013aMalehmir et al. ( , 2013b have shown that the coarse-grained layer extended locally in a 10 restricted area, but this work shows the extension of this layer to the north and south of the initial study area. The coarsegrained and bedrock horizons were picked on the processed land and river seismic lines, and elevation surfaces were interpolated using the seismic, borehole (BGA, 2018) and LiDAR data (© Lantmäteriet). Total sounding data identify top and bottom of the coarse-grained at many points at the site. The LiDAR data were mainly used for fixing the elevation of the rock outcrops. The surfaces for the top of the coarse-grained layer and top of bedrock were calculated using a natural 15 neighbour interpolation after a Delaunay triangulation of the scattered sample points was generated. Figure 12 shows the results of this modelling together with the 3D visualization of the seismic profiles. The bedrock surface in Fig. 12c undulates between 80.5 and -110 m elevation. Two elongated depressions next to the river, which cross lines 2-2b, 5-5b, 6 and 7, can be identified. These depressions are interpreted as possible faults and coincide with the position of fracture zones (Fig. 2a).
The gentler coarse-grained layer surface in Fig. 12d ranges from 18.5 to -28.5 m elevation. The data are better constrained in 20 the area surrounding the rock outcrop, as more seismic lines are available there. The bedrock surface is visible in all the lines, except line 4 (Malehmir et al., 2013b) and, therefore, the model of the bedrock surface in the study area is generally well constrained. The coarse-grained layer is not identified in the northwestern part of line 2-2b and line 6, but the model gives a good overview of the layer extension, which spreads over both sides of the river, and is an important feature in studying quick-clay landslides. 25 The maximum elevation for both the bedrock and coarse-grained layer surfaces coincides with the centre of the survey site, and the undulated bedrock dips down towards the river. This implies that more water may flow in the coarse-grained layer closer to the river. Löfroth et al. (2011) andSalas-Romero et al. (2015) show that the coarse-grained layer is thicker within the depressions, which is related to the deeper top of bedrock and sediment focusing when deposition took place. The thickness of the coarse-grained layer and the higher water flow could increase the thickness of potential quick clays in those 30 depressions. The possible faults indicate areas more susceptible to slide, due to slope inclination and/or increased water flow. Figure 13 shows a view of the 3D modelling from the north. Figure 13c shows the interpolated elevation surface for top of bedrock along the river. Note the bedrock undulation between lines 6 and 7, whose reflection seismic results ( Fig. 7 and 8 indicate 3D effects in the western part of the profiles due to rough topography. Figure 13d shows the delineation of the coarse-grained layer along the river; the reflections corresponding to the filled channels correlate with the interpolated top of the coarse-grained layer surface (see Fig. 13b and 13d).

3D Hydrological modelling of the coarse-grained layer
After obtaining the elevation surface for the top of the coarse-grained layer, we modelled the elevation surface for the bottom 5 of the layer using the RMT resistivity (Lindgren, 2014;Shan et al., 2014;Wang et al., 2016) and available borehole data (BGA, 2018;Salas-Romero et al., 2015). Thickness values of the coarse-grained layer were picked along the RMT resistivity profiles at its estimated position. The thickness of the layer was then interpolated together with thickness values obtained from the borehole data. The interpolated thickness surface was subtracted from the elevation surface of the top of the coarsegrained layer previously modelled in order to obtain the elevation surface of the bottom of the coarse-grained layer. 10 The elevation and thickness values for the coarse-grained layer were used for obtaining a single-layer two-dimensional groundwater model (Fig. 14a), which reflects a gradual decrease of the hydraulic head from the outcrop area to the river. The horizontal model resolution is 10 m. Groundwater table from the existing boreholes in the study area (see Fig. 2b where the hydraulic head (h) is the unknown variable, was solved using a finite volume method (Guyer et al., 2009). The transmissivity (T) was defined as the product of the local interpolated coarse-grained layer thickness with a uniform 20 hydraulic conductivity (K), the latter needed to be calibrated (Fig. 14b). The transmissivity values are higher (from 0.006 to 0.016 m 2 /s) around the land seismic lines, due to a thicker coarse-grained layer at these positions. As hydraulic boundary conditions, the cells directly underlying the river were assumed to have a fixed head corresponding to the average river level as shown in Fig. 2b. The central part of the model is characterized by the disappearance of the coarse-grained layer, a thin sandy-silty till cover and several elevated rock outcrops (Fig. 2a), which we hypothesized to be a groundwater recharge area 25 for the coarse-grained layer by infiltration along the bedrock/sediments interface. The area of the considered recharge zone , ( 2)  10 which is approximately 20 years, assuming a porosity (phi) of 0.2 (or 20 %). This relatively short residence time would point to lower salinity groundwater occurrences in the coarse-grained layer compared to the overlying clays and ion transfer from the clays to the underlying groundwater flow system, either by diffusion or by slow infiltration (Torrance, 1979), which has been identified as a precursor to the formation of quick clays (Rankka et al., 2004). Figure 14c shows the values of the mean groundwater velocity (Darcy flow vector amplitude divided by phi) and vector field 15 of the Darcy flow, whose directions go from the outcrop area to the river. At positions where T (or thickness of the coarsegrained layer) is lower (less than 0.006 m 2 /s), the mean groundwater velocity is higher (from 0.00005 to 0.00015 m/s), and vice-versa, where T is large (from 0.006 to 0.0162 m 2 /s) the velocity is very low (less than 0.00012 m/s). Assuming that the leaching of marine salts increases with groundwater velocity, areas where the groundwater velocity is higher could be at an increased risk of quick-clay formation. 20

Morphology of the Göta River valley
The total-field magnetic data were corrected for differences in diurnal variations and instrumental drift using the base station data (a background, International Geomagnetic Reference Field-IGRF, value of 50600 nT, Earth magnetic field, was subtracted from the results to convert to residual magnetic anomaly data). However, several inconsistencies were still present in the corrected data such as different values at overlapping positions, level jumps between measurement days (see sketch 25 with the measurement and base station positions in the lower right corner in Fig. 15), and elongated features parallel to the measuring paths. In order to level the data, a constant value was added or removed in the measurements for the last three days, and the polarity was changed for the data of the first day. For removing the elongated features, the data were divided in two groups, the first three days and the last two days of measurements, gridded and filtered similar to the micro-levelling procedure (Minty, 1991). A low-pass filter was applied in N-S direction, a high-pass filter in the E-W direction, and then the 30 result was subtracted from the original gridded data. The final result (Fig. 15) is smoother and more homogeneous than the initial data but still has few elongated features, which are residual errors (acquisition footprint) and not natural features as they coincide with the sampling directions. Figure 15 shows that the residual magnetic anomaly values are higher on the northern part than on the southern (ranging from -20 to 20 nT); at the bottom and in the eastern flank of the landslide scar that crosses line 5-5b the values reach 20 nT.
Almost all along line 4 and between lines 2-2b and 5-5b higher residual magnetic anomaly values are found. Salas- Romero 5 et al. (2015) showed that the coarse-grained layer has higher magnetic susceptibility compared to the sediments above and below of these materials. Besides, we also took samples at the bottom of the landslide scar up to 1.5-2 m depth that were identified as silty-sandy. The high residual magnetic anomaly values at the landslide scar may indicate that the coarse- At the latter borehole, the thickness of the coarse-grained layer reaches almost 10 m (in BH1 and BH3 the thickness of this layer is around 1 and 3 m, respectively). The shallowest tops of the coarse-grained layer are registered at borehole 7202 at the landslide scar and at BH1. Comparing this information with the residual magnetic anomaly data, we infer that the coarse-20 grained layer, its distance to the surface and thickness, may be related to the high values of the magnetic data in the northern part and around BH1 where line 1 lies. The bedrock at these positions is quite deep to cause such high values (e.g. in BH2 the top of bedrock is around 78 m). The southwestern part does not reflect the same behaviour, which may be related to the thinness of the coarse-grained layer and/or its depth. On the southern part of the residual magnetic anomaly map an elongated anomaly that follows SW-NE direction is observed. The values are higher in the centre (ranging approximately 25 between -15 and 5 nT), with the maximum values around borehole 7067 (BGA, 2018) in the intersection with line 2-2b, and lower around the anomaly (ranging from -25 to -15 nT). At borehole 7067, bedrock is close to the surface, with high residual magnetic anomaly values coinciding with the bedrock topography. We interpret the elongated anomaly to be related to the scarp formed between bedrock and the lower elevated sediments to the west (Fig. 2). The southeastern part of the residual magnetic anomaly map where there are several outcrops and the surface elevation is higher, includes negative and positive 30 magnetic anomalies. A few houses and farms may have influenced the residual magnetic anomaly data in this area. Figure 16 presents three examples of combining the side-scan sonar (© SGU) with the bathymetric data (© SGI) on the river (see positions in Fig. 2c). The first example, Fig. 16a-e, is a section that is crossed by line 5-5b. Deposits of unclear origin can be observed at the bottom of the section (Fig. 16a); their granular texture and darker colour indicate that they may be harder and denser than the surrounding materials. These deposits may proceed from the landslide scars in both sides of the river (Fig. 2) and/or from the discharge of sediments transported by the gullies or tributary intersecting the Göta River at this position. Slopes in profile AA' can be classified as "high terrace-steep slope" (Millet, 2011), with values ranging between 30° and 45°. Profile BB' (Fig. 16d-e) shows the same type of slope on the northern riverbank, and a gentler slope (the slope is a mix between "high terrace-steep slope" and "straight un-even profile", Millet, 2011) on the opposite side. The B' 5 extreme coincides with the position of a stream (Fig. 2). The toe of slope probably contains material due to the collapse of the subaquatic slope or sediments deposited by the stream. The second example, Fig. 16f-j, is a section located south of the study area. Profile AA' shows a possible subaquatic landslide scar in the western side. Figure 16g-h shows a "double terrace" (slopes between 40° and 55°) on the western side and a "high terrace-steep slope" (inclination around 47°) on the opposite side. The deepest terrace in the western side has a ledge that is around 5 m high, which coincides with the position 10 of the identified subaquatic landslide scar. Profile BB' (Figure 16i-j) shows accumulated material against the riverbank in the eastern side. The slope on the western side can be classified as a "high terrace-steep slope" (slope ~50°), and the slope profile on the opposite side resembles a combination of the classes "high terrace-steep slope" and "straight un-even profile" (maximum slope is around 30°). The toe of slope seems to consist of landslide deposits. The third example, Fig. 16k-m, is a section even more to the south than the one in Fig. 16f-j. Accumulated material is visible at the bottom of the river in the 15 eastern side in profile AA' (Figure 16l). The inclination of the slope is very irregular, generally below 20° but with some parts having higher inclination. The slope looks like a "straight un-even profile", although there are parts with small terraces.
The toe of slope appears to have formed from landslide deposits. The opposite side resembles a "high terrace-steep slope" (slope is 45°).
Erosion and landslide processes have formed the landscape of the Göta River valley (SGI, 2012a). Land and river seismic 20 data, together with side-scan sonar and bathymetric data give a good overview of the (sub-)surface in this valley. Along the river filled channels are identified, which were probably formed when the riverbed morphology changed over time. The bedrock at the river channel shows several fracture zones. The slopes of the riverbanks are generally steep and many subaquatic landslide scars and deposits can be found along the river. The origin of these deposits may also be related with the remains from the erosion protections placed between 1960 and 1970 along the Göta River. The likelihood of 25 retrogressive landslides inland can increase due to undercutting of riverbanks during high discharge or wave erosion generated by shipping movement, which reduces lateral support and causes more instability (SGI, 2012a). At the surface, the inclination of the slopes is influenced by the land use and precipitation induced processes (SGI, 2012a).
According to SGI, our study area has, in general, medium landslide risk. Close to the river the risk is higher due to the presence of highly sensitive clays or quick clays. SGI has evaluated the risk of landslides along the Göta River under 30 different climate change scenarios (2012a, 2012c). These scenarios estimate increases in temperature by 4-5° and 20-30 % more precipitation by 2100. High and low drainage levels from Lake Vänern will be more frequent, sea level will rise up to 0.7 m at Göteborg, and maximum groundwater levels and pore pressure in slopes will not change significantly. These has a great impact to the south of Lilla Edet, and under these climate change scenarios will be more intense along the river's course (SGI, 2012a). This means that although the study area is located to the north of Lilla Edet, where erosion has less impact, any small change in the erosion rate in the future could cause serious effects as this area is already considered to be at medium-high landslide risk.

Conclusions 5
Through an extensive reflection seismic investigation, which includes land and river lines and their combination with other geophysical, geotechnical and borehole data, this study allows the delineation in a regional scale of a coarse-grained layer, underlying bedrock and fracture zones in an area prone to quick-clay landslides in southwest Sweden. This is the first time in Sweden that land and river reflection seismic data are combined for studying the subsurface associated with this type of landslides. 10 Some of the geological and geohydrological prerequisites for the formation of quick clay in nature specified by Rankka et al. (2004), are shown in the results of this study. Correlation of reflection seismic, resistivity and P-wave refraction tomography results offers information about the presence of underlying coarse-grained layers, peaks in the bedrock surface, and approximated thickness and type of clay deposits. 3D modelling of the elevation surfaces for the coarse-grained layer and bedrock illustrates the possible infiltration points in the area, as nearby elevated rock outcrops or fractures. Hydrological 15 modelling of the coarse-grained layer estimates the size of the catchment area and the dominant leaching processes for the low-water season (diffusion and slow infiltration). The formation of quick clays is more significant under artesian groundwater conditions, which may be dominant in the high-water season (summer and autumn) at the survey site. Ground magnetic data delineate coarse-grained materials and bedrock topography. The northern part of the study area contains a shallower and thicker coarse-grained layer. At the bottleneck landslide scar present in the centre of the survey, the high 20 residual magnetic anomaly values indicate the presence of the coarse-grained layer, which may have acted as sliding surface together with quick clays. The side-scan sonar and bathymetric data reveal a number of distinct morphological features in the Göta River valley, that reflect the erosional processes, landslide scars and mass-movement deposits.
This work illustrates the significance of studying subsurface geology, including features within bedrock that are often overlooked when investigating landslides, especially ones that involve quick clays. 25 Author contributions. SS and AA participated in the acquisition of the land reflection seismic and magnetic data. AA designed the fieldwork campaigns in 2011 and 2013 in the study area. SS processed the land and river reflection seismic data with the support from AA. SS performed the geological modelling. SS analysed, corrected and processed the magnetic data. 5 SS prepared the data used for the hydrological modelling, which was performed by BD. BD wrote most of the hydrological modelling section. SS made an integrated interpretation of the geophysical, geotechnical, geological and hydrological data with the help of all co-authors. SS is the main contributor to the writing of this article. All co-authors contributed to the final version of this article.
Competing interests. The authors declare that they have no conflict of interest. 10