Seasonal velocity patterns and deforming bed processes associated with different subglacial drainage systems.

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Jane Hart, Nathaniel Baurley, Amy Bonnie, Benjamin Robson, Graeme Bragg, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4539760/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Mar, 2025 Read the published version in Communications Earth & Environment → Version 1 posted You are reading this latest preprint version Abstract We use a series of unique techniques (wireless in situ subglacial probes; web connected GNSS) along with remotely sensed data to record a continuum of subglacial hydrology from channelized to braided behaviour associated with four soft bedded temperate glaciers. We argue this continuum may be affected by till grain size and subaqueous processes. In addition, we are able to quantify sedimentary processes associated with these different hydrologies. Although we have used a multi-data stream here, we suggest it is possible to solely use glacier velocity data, derived from Sentinel-1 imagery, to distinguish the different hydrological types. This is important because the water at the base of the glacier (in both water bodies and the till) is a key driver of glacier behaviour and the rate of sea level rise, but direct measurements of the basal environment are rare, hence the importance of our remote sensing data. Earth and environmental sciences/Hydrology Earth and environmental sciences/Climate sciences Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction As glaciers worldwide melt in response to climate change, it becomes increasingly vital to determine their present and future contribution to sea level rise 1 , 2 . These higher temperatures will lead to increased melting of the glacier, generating additional meltwater which can flow to the glacier bed, but there is no linear relationship between surface melt and glacier response 3 . This is because of numerous factors within the glacial system, but in particular the behaviour of water and till at the glacier base 4 , 5 which control the ‘slipperiness’ of the glacier bed (sliding laws) 6 , 7 , 25 . Glaciers can flow over either rigid or unconsolidated bedrock (soft- beds). It has been a longstanding assumption that the subglacial hydrology of rigid beds comprises a predominantly channelised drainage in the summer 9 , 10 . In contrast, it has been suggested that soft-bedded glaciers have a distributed system, based on observations from Antarctic ice streams 11 , 12 , 13 , 14 and mountain glaciers 15 , 16 . In addition, recent research on rigid-bedded glaciers from Greenland, suggests that distributed drainage exists alongside channelized during the late summer 17 , whilst simultaneously new examples of soft beds are being discovered across Greenland 18 and many glaciers worldwide rest on mixed bedrock. These observations highlight that the subglacial hydrology for all bed types is more complex than initially envisaged, and there is a need to identify different subglacial hydrologies to understand glacier behaviour. Meltwater draining into the subglacial till changes the effective pressure (normal pressure minus water pressure) of the glacier. As effective pressures range from low to high, so behaviour changes from sliding, to deformation, to stick (no/little motion) 19 , 20 . It has been shown by numerous researchers that glaciers move via stick-slip motion 21 , 22 , due to tidal or meltwater processes 23 , 24 . A study of Skálafellsjökull, a temperate soft-bedded glacier 16 , showed that stick-slip motion occurred on a daily scale during the melt season and on a multi-day scale in winter. This process comprises both sliding and deformation, with the authors able to calculate the percentage times that these processes occurred throughout the season. In light of the importance of the role of the sliding law parameters in sea level rise predictions 6 , 7 , 8 , there have been a number of recent discussions of the sliding (basal friction) law 25 , with a recent model 26 proposing a single law to describe behaviour for both rigid and soft beds. However, any sliding law needs to include changing bed conditions to enable realistic parameterization. We examine a series of soft-bedded glaciers in maritime locations and use a range of techniques to investigate their seasonal behaviour. We are able to show a continuum between braided/multichannel and channelized systems. We argue the dominant controls on this range are till grainsize and subaqueous processes. The braided system is characterised by dramatic speed-up events during warm days during winter (winter events), a delayed and slow spring event, relatively stable summer velocities, and peak velocities during autumn. This is because during summer an anastomosing system develops which can adapt to meltwater changes, promoting stable velocities and facilitating water storage. This water is released during the winter allowing winter speed-up events, with a period of recharge needed during spring. In contrast, the channelized system has few/no winter speed-up events, a fast-spring event at the beginning of spring, a declining velocity over the summer, and similar peak velocities during autumn. Within a channelized system, the connected area increases over the summer (reducing velocity), but has much lower storage, hence fewer winter events, and a dramatic spring event once temperatures and meltwater increase. We are also able to quantify subglacial processes and use these, alongside the hydrological findings, to understand till and glaciofluvial sedimentology. In addition, using the results from our multi-data stream analysis, we propose that it is possible to identify the subglacial hydrological systems from the analysis of Sentenal-1 data alone. Results Field Sites We report the results from four temperate soft-bedded glaciers in relatively mild maritime locations (Fig. 1 ), using field based and remotely sensed data. We have studied three adjacent glaciers from the Vatnajökull ice cap, Iceland: Skálafellsjökull 16 , 27 , Fjallsjökull and Breiðamerkurjökull. All three calve into proglacial lakes, approximately 20m, 100m, and 300m deep respectively 28 , 29 . The fourth glacier is Briksdalsbreen, Norway; which is an outlet glacier of the Jostedalsbreen ice cap 30 , 31 , and also calved into a 20m deep proglacial lake. The field study of Briksdalsbreen took place 2004-6, and since then the glacier has dramatically retreated onto a plateau, so we have derived the remotely sensed velocity from the nearby Nigardsbreen. Details about the sites are shown in Table 1 . All four glaciers rest on a till base and have a foreland geomorphology composed of flutes and push moraines, indicative of subglacial deformation 30 , 32 . Field data was collected via the Glacsweb environmental sensor network 33 which comprises sensor nodes that relay their data to a sensor network server in the UK. This included in situ sensor nodes (Glacsweb probes) inserted into the till (0.16 m long) which contained micro-sensors measuring water pressure, probe deformation, resistance, tilt and probe temperature 34 , 16 . Here we discuss the water pressure results, measured in hydraulic head (m) and then compared with the water column height from the known glacier thickness (flotation pressure %). We also calculate the effective pressure N, which is the ice overburden pressure minus water pressure. The system also included geophones to measure ice-quakes 35 . Secondly, we designed and built a web connected real time kinematic GNSS which was part of an Internet of Things (IoT) system 36 . Details of sensors, readings, locations and errors are discussed elsewhere 27 , 16 , and details of the data sets are outlined in the ‘Methods’. Table 1 Details about the four sites Field Site Data period Mean annual air temp. ( o C) * Glacier area (km 2 ) Altitude of study site (m) GPR Glacsweb Probe data Velocity Till mean Grain size (µm) GPS Sentinel − 1 Skálafellsjökull 64.251 o N, 15.832 o W 2008–2014 -0.1 ~ 100 28 792 27 ✓ ✓ Leica System 1200 ✓ 53 27 Fjallsjökull 64.011 o N, 16.428 o W 2017–2023 5.1 ~ 45 28 89 x x Web connected RTK ✓ 178 Breiðamerkurjökull 64.099 o N, 16.324 o W 2017–2023 4.6 ~ 900 37 173 ✓ x Web connected RTK GPS ✓ 88 Briksdalsbreen 61.663 o N, 6.864 o E (Nigardsbreen 61.884 o N, 7.193 o E) 2004–2006, 20172020 5.7 (1.9) ~ 15 31 (~ 48 38 ) 375 31 ✓ ✓ x ✓ 1600 31 *Data from the site over the study period, taken from the local metrological station, corrected for altitude/local conditions from weather station on the base station. Figure 2 shows the annual pattern of air temperature, till water pressure, and daily velocity for each glacier (where available) plotted from 1st September (DOY 244) (2009/10 for Skálafellsjökull, 2017/8 for Fjallsjökull and Breiðamerkurjökull, and 2004/5 for Briksdalsbreen) whilst the annual 12 day velocity data from Sentinel-1 SAR imagery for each glacier for 2018/19 is illustrated in Fig. 3 . We have defined the seasons for the four glaciers based on air temperature, which is related to melt 39 . Since these glaciers are in different locations/altitudes the detailed thresholds are discussed in the Methods. Skálafellsjökull The annual pattern of water pressure, effective pressure and velocities are shown in Figs. 2 a and 3 a. Winter comprises two states. A base state with high till water pressure and low velocity, and speed-up events where water pressures dramatically decrease and velocities increase. These speed-up events occur every time the temperature rises above zero (83% of the time), 12-day velocity data, with an 84% correlation (see Methodology for details). Alongside these events, it has been reported that there is a vertical rise of the glacier and high discharge 27 , and a pattern of initial antithetic (backwards) tilt change and then synthetic (forwards) tilt change 16 . During the spring there is also a velocity increase, but this is within the upper range of the winter event velocities. This speed-up occurs ~ 17 days after the beginning of spring and is not related to a specific weather event. In summer, water pressures remain consistently high whereas velocities are high at the beginning of summer but gradually decrease across the summer period (24% reduction, 12-day data). In contrast, till water pressure slowly decreases during autumn, but velocity peaks are some of the highest. The effective pressures are low in the summer and high in the winter and have a very similar in pattern at each probe 31 . Figure 4b illustrates the mean melt season diurnal tilt change, air temperature and velocity patterns. Air temperatures were lowest at 07:00, rising to a high plateau 12:00–17:00, cooling rapidly until 21:00, then cooling more slowly until 07:00, with a small rise at 04:00. Velocities were also low in the morning, rising to a peak at 13:00, and then decreasing throughout the afternoon and evening, before a speed-up event at 4:00. The tilt-changes are generally low during the main high velocity event at midday, but high during slow down and speed-up period. These high tilt changes correlate with high ice quake events 16 . Results from GPR studies 40 and net inputs and outputs 27 indicate that Skálafellsjökull has a braided subglacial hydrology. During the summer, discharge only accounts for approximately 60% of inputs. The excess goes into the aquifer, the subglacial till, and the braided system itself in a series of backwater reservoirs. Water from the till and the reservoirs is partly released during winter, where discharge is 5 times larger than inputs. Fjallsjökull The annual velocity patterns are shown in Figs. 2 b and 3 b. During winter there is a distinct base velocity, with speed-up events (~ 6 times faster than the base), predominantly related to high air temperatures (temperatures > 5 o C), for both the daily (77% correlation) and 12-day (80% correlation) velocity. There is an average of 11 events per year, with an average length of 17 days. Detail of one of these events is illustrated in Fig. 4c. There were speed-up events ~ 13 days after the beginning of spring (‘spring event’), but these are similar to the smaller winter event speed-ups which mark the beginning of the melt season when velocities rise to a higher mean level. Summer velocities are relatively stable, with a slight decrease over the season (daily velocity 45%, 12-day velocity 7%). Velocities were also high during autumn, likely to be related to weather conditions. The mean summer diurnal pattern of velocity and air temperature is shown in Fig. 4d (mean of 2023 results). Air temperatures are lowest at 04:00, slowly rising throughout the morning to a high temperature plateau between 13:00–15:00 and then decreasing overnight. At Fjallsjökull, the velocity was also lowest in the early morning (06:00), and rising to a peak at 15:00, and then decreasing overnight. The peak velocity occurred 1–2 hours after peak air temperatures. Note the air temperature data is hourly whilst the velocity data is every 3 hours. Breiðamerkurjökull At Breiðamerkurjökull there are fewer and relatively slower winter speed-up events (approx. three times faster than the base velocity), and many are unrelated to meteorological conditions. The correlation for the daily velocity and air temperature is only 61% and 58% for the daily and 12-day scale, respectively. When a speed-up event does occur in response to increased temperatures, it occurs almost immediately (Fig. 4c) and there are often other speed-up events within one winter event. There was a speed-up event at the beginning of spring associated with the rise in air temperatures, marking the beginning of the higher melt season velocities. This was recorded in the daily velocity from 2018, and occurred on the 8th May (DOY 128), which was equivalent to the 90% percentile of the winter events, followed by a much faster speed-up event on the 13th May (DOY 133) (140% larger than fastest winter event). This latter event occurred after five days of high temperatures and rainfall. In the 12-day data this occurred in the 8th -20th May period in 2018 (DOY 128–140) (equal to maximum winter event velocities), 27th May-8th June period in 2019 (DOY 147–159) (highest velocity of the year) and 9th -21st May period in 2020 (DOY 130–142) (top 80% percentile of winter events). These all occurred once temperatures rose above the threshold. Summer velocities, meanwhile, are relatively stable, with a slight decrease (daily 34% and 12-day 4%), whilst autumn velocity patterns are intermediate between summer and winter. At Breiðamerkurjökull, the diurnal velocity pattern (mean summer 2023) was different to that observed at Fjallsjökull (Fig. 4d). The velocity had a double peak, rising during the afternoon to a peak at 18:00 (4 hours after peak temperature), then decreased during the evening before rising to a second peak during the night (03:00). Briksdalsbreen Figure 2 d shows the annual air temperature (2004/5) plotted against the till water pressure from two probes: B8 (2004/5) and B12 (2005/6). The in-situ tilt data from these probes 31 was used to investigate subglacial processes. Although a TOPCON GPS system was installed at the site, the data was only resolved at a monthly scale and so is not used here. The field study took place before Sentinel-1 was launched, so there are no available satellite images of the glacier from 2004/5 with which to calculate velocity at a comparable temporal resolution. In light of this, we utilise Sentinel-1 velocity analysis of the nearby Nigardsbreen glacier, as it is of a similar size, altitudinal range and aspect to Briksdalsbreen during the early 2000’s. During the winter, the till water pressure was approximately zero for probe B12, whilst at B8 it was generally low, except for a series of dramatic increases that occur when the air temperature declines below zero. There were four events during 2004/5 (DOY 321–352, DOY 353 − 18, DOY 19–42, and DOY 43–80), with details of one of these events illustrated in Fig. 4e. Initially, there was a period where temperatures were below zero, followed by a phase of above-zero temperatures. Once temperatures fell below zero, there was a mean four-day lag before water pressures increased. This was accompanied by an antithetic (backwards) tilt movement lasting one day and then a large synthetic (forward) tilt movement also lasting one day, followed by a period (mean length 16 days) of low synthetic tilt during the sub-zero temperatures. Once temperatures rose above zero, water pressure rapidly declined, and there was a repeat pattern of one day antithetic tilt followed by one day of synthetic tilt. After this, there was a long period (mean length 18 days) when the water pressures were low, with low synthetic tilt. During the spring, water pressures rise as air temperatures increase. For probe B8 the rise is relatively slow (2.9 m floatation pressure % per day), whilst at B12 there is a double event. A one-day dramatic rise and fall on DOY 68, followed by an abrupt rise on DOY 86 (36 m flotation pressure % per day) which marks the Spring event. A similar pattern was also seen at probe B10 (not shown here but reported elsewhere 31 ), which showed a double peak but with different timings (initial rise and fall DOY 106, main abrupt rise DOY 117). Summer begins with high pressures (~ DOY 111–175), which slowly decrease in mid-summer (~ DOY 176–223), then rapidly decrease in late summer (~ DOY 224–240). During the autumn (DOY 241–320), till water pressures are either high (B12) or zero (B8). The effective pressure has a distinct record. In summer probe 8 the water pressure exceeds the local overburden pressure (negative effective pressure) known as excess water pressure. Whilst for probe 12 the effectives pressures are low (but positive) in the summer but are over pressurized in autumn. During winter, in each probe, effective pressures are high. Figure 4f shows the mean summer mean air temperature and tilt. Air temperatures rise in the morning (04:00 to 12:00), peak in the afternoon (12:00 to 16:00) and then decline overnight (16:00–04:00). The tilt change pattern shows least movement in the night (04:00), slowly rising in the morning (04:00–12:00), peaking at 16:00, and then falling. The autumn tilt changes from probe 12 show a similar pattern, but with more extreme changes, with a secondary peak in tilt during the early morning (04:00). In winter, the 12-day velocity data (Fig. 3 d) varies throughout the season but only has a low, 54%, correlation with temperature data. In spring, there is a fast speed-up event equal to or greater than the winter events, which occur during the first 12-day period of spring each year. Velocities tend to decrease over the summer (38%) and rise again in autumn. Previous results from GPR studies 31 indicate that Briksdalsbreen has a channelized subglacial hydrology. Discussion The growing recognition of braided/multichannel river systems associated with soft-bedded glaciers in Antarctica 11 , 12 , 13 , 14 , 7 could lead to a possible assumption that all soft-bedded glaciers have such a system. However, we have demonstrated here that this is not the case, and that there is likely a continuum between a distributed and a channelized system (Fig. 5 ). We will now discuss the different seasonal behaviours associated with this continuum, suggest some controlling factors, outline how it is possible to identify the separate regimes based on velocity records, and quantify and identify different subglacial sedimentary processes. The results from Skálafellsjökull provide evidence of the seasonal development of a braided river system associated with a soft-bedded glacier (Fig. 5 a). During the summer, the level of anastomosing is related to melt, and large parts of the bed have high connectivity. At the beginning of summer, as the channels are opening, melt increases lead to velocity increases. However, later in summer, the high levels of melt results in enhanced anastomosing, with a resultant velocity decline. Whenever the melt exceeds the carrying capacity of the system, this leads to reduced effective pressure and summer speed-up events 42 , 43 . During autumn meltwater inputs decrease, meaning the level of anastomosing also decreases, as well as the connectivity, with water flow concentrated along the main channels. As a result, water may become isolated in backwater elements (‘ponds’), whilst it will also drain out of the till resulting in decreased water pressures. High meltwater inputs at this time result in the fastest peak velocities because in this transitional state the subglacial system is easily overwhelmed 42 , 43 . During winter, as there is little meltwater generated, there is low flow through the main channels and the till, resulting in low velocities. However, during winter events there are speed-up events with shear-induced till dilation 20 , glacier uplift and high discharge. Water is released from the subglacial reservoirs, which include the till, cavities, macroporous sources and the ponds. These become ‘connected’, and water is able to flow at the ice/till interface into the main channels. During spring the meltwater input increases, being accommodated within the main winter channels whilst connectivity within the till increases, until a threshold is passed (after ~ 17 days), and then a speed-up (spring) event occurs. Afterwards, the system adapts to the new higher melt levels associated with summer via the anatomising of the channels. The pattern of behaviour at Fjallsjökull was very similar to that at Skálafellsjökull, with the winter speed-up events, a non-weather-related spring event occurring ~ 13 days after the beginning of spring, relatively stable summer velocities, and high autumn velocities. Because of this, we suggest that this also has a braided river system. Breiðamerkurjökull is adjacent to Fjallsjökull with similar weather and bedrock conditions and thus would be expected to have comparable glacier behaviour. However, there are several key differences. This includes a lack of winter events and a distinct spring event related to weather conditions, a dual peak in summer diurnal temperatures (9 hours apart), whilst there are also numerous small speed-up events unrelated to weather conditions that occur during both summer and winter. We suggest that the difference in response is due to the presence of the deep proglacial lake Jökulsárlón at Breiðamerkurjökull. It has been shown that deep lakes generate high hydrostatic pressure which leads to lake water being pushed up-glacier into subglacial channels 44 , 45 . At the same time, high summer temperatures and rainfall will generate high discharge. Towards the margin, the bed could become over pressurised to enable the meltwater to be evacuated from the glacier. We suggest that the braided system switches to a more effective channelised system when meltwater input is high, releasing the excess melt water in short bursts. This allows any summer excess meltwater to be drained into the lake rather than be stored with the subglacial system. In addition, calving associated with the interactions between the glacier margin and the proglacial lake may help explain the non-weather-related speed-up events 46 , 47 . Increased velocity would encourage crevassing, allowing additional meltwater to reach the bed, as well as increasing the buoyancy of the glacier margin. Although Jökulsárlón has a tidal influence with two high tides a day 48 , which could potentially affect the glacier, it would be expected for these to occur 12 hours apart, but even out over the season as the timings of tidal peaks change each day. As such, we suggest the dual peaks recorded in the summer diurnal pattern likely reflect the dominance of two water pathways. There is an initial velocity increase associated with midday melting, but much of the water is prevented from draining due to high hydrostatic pressures from the lake. This excess water builds up during the night until a threshold is passed, after which channelized drainage dominates. We suggest the following seasonal pattern (Fig. 5 b): During summer there is a braided river system, but when melt is high, channelization occurs, which also drains any storage. In autumn, the anatomising decreases to a few main channels. During winter, these channels continue to shrink, but due to the lack of storage during times of melt, there is limited glacier response in terms of speed-up events. During spring the anastomosing increases, but the presence of high melt associated with warming causes a dramatic spring event, which cause the subglacial system to be overwhelmed. In contrast, Briksdalsbreen reflects typical channelized behaviour (Fig. 5 c), with the till water pressure data indicating two distinct regimes within the system. The results from probe B8 reflect ‘highly connected’ behaviour from a site close to the main channel (Type A) whilst those from B12 reflect ‘weakly connected’ behaviour away from the main channel (Type B). At the beginning of summer (for both Type A and B behaviour), the water pressure is high, however, as the summer progresses till water pressures slowly decrease. There are high velocities at the beginning of summer, followed by a velocity decline as the summer progresses. This is similar to the pattern described from Greenland, where in early summer, meltwater is able to lubricate the bed, resulting in basal sliding 49 , whilst later in summer, this meltwater can be accommodated by the subglacial system via the growth of the ‘weakly connected’ distributed drainage 10 , 17 so velocities are reduced 50 , 51 . As autumn approaches, close to the main channels, the till water pressure drops as these channels reduce in size in response to reduced meltwater inputs. However further away from these channels, the decrease in water pressure is slower as the system takes longer to adapt. Once autumn is established, any warm day will result in dramatic increases in velocity as the system is easily overwhelmed by meltwater inputs. Close to the main channels these high meltwater inputs drain into the channels and connected till, but away from the main channels these water inputs cannot easily drain, and so till water pressures rise. During winter, temperatures remain above zero, so a small amount of water is generated by melt, as well as heat from glacier movement, and so the conduits remain open, although with much lower discharge. This results in low till water pressures, although some of this meltwater can drain through the till into the main channels. However, when temperatures are sub-zero, melt decreases, and the conduits begin to close. This means sites close to the main channel have their drainage restricted and water pressures rise, whilst those further away do not change, as any change in melt is distributed evenly through the till. During spring, the area surrounding the main channel slowly adjusts to the increase in water input associated with spring melt (Type A), as parts of the main channel may not have completely closed during winter. In contrast, sites further from the main channel have a more dramatic response to meltwater input, as the area will become rapidly connected (Type B). This will occur at different times, associated with water accumulation and specific water passage through the till. At first, the channels cannot accommodate the extra discharge, and so there is a rapid increase in till water pressure, and possibly a speed-up event. Subsequently, the system becomes adapted to the high melt and water pressures can remain high. There have been numerous theoretical attempts to establish the characteristics that determine whether a channelized or distributed system will form associated with soft beds 52 , 53 , 54 . These investigate the relative properties of ice and sediment and ice surface slope. We suggest that our results indicate the importance of sediment grain size. The subglacial till at Briksdalsbreen is coarse (very coarse sand) and we suggest that at the beginning of the melt season, as the distributed system grows, a low pressure channel is formed from sediment erosion. This rapidly draws water from the surrounding till, and this channel remains relatively stable 54 . This results in spatial variation in subglacial till water pressures across the bed, including areas of over pressurization. In contrast, at the Icelandic sites, the presence of the finer grained till (ranging from coarse silt to fine sand) results in the development of the multichannel form and a spatially similar low summer effective pressure pattern. We propose that the members of this subglacial hydrology continuum have a set of distinct velocity patterns that may be used to identify the subglacial hydrology in regions where air temperatures periodically rise above zero during winter (Table 2 ). The difference between the braided system and the better-known channelized system is as follows: Since water is stored in the braided system itself, this is released in a series of winter events which are either absent from the channelised system, or fewer in number. By spring, much of the stored water in the braided system has already been released, and so a period of spring melting is required to generate enough water for a speed-up event. In contrast, in the channelized system the spring inputs immediately overwhelms the capacity of the system, resulting in a fast and distinct speed-up event. In summer, in the braided system, the constantly changing anastomosing allows the velocity to remain relatively stable, whilst in the channelized system, the development of the weakly connected drainage reduces the velocity. However, by the end of summer the systems are relatively so autumn velocity increases are observed in both systems. Table 2 – Criterion to identify subglacial hydrology based on seasonal velocity changes Braided Drained Braided Channelized Winter Winter events No/few winter events No/few winter events Spring ‘Slow’ speed-up event ~ 15 days after the beginning of spring ‘Fast’ speed-up event at the beginning of spring ‘Fast’ speed-up event at the beginning of spring Summer Slow decrease over the summer Slow decrease over the summer Fast decrease over the summer Autumn High velocities High velocities High velocities Since Breiðamerkurjökull has a drained braided subglacial hydrology it demonstrates a mix of the criterion. As it has low storage, there is limited response to winter events and a dramatic early spring event similar to the channelized system. However, during summer it behaves in a similar way to the braided system and has a relatively constant summer velocity as a result. Stick-slip motion was observed at Skálafellsjökull throughout the year driven by meltwater and comprised four phases. During the melt season this occurred on a diurnal scale, with meltwater entering the system in the morning, which continually increases until a threshold is crossed, at which point the subglacial hydrology is overwhelmed, and there is a period of glacier sliding (Phase 1). Subsequently, the glacier reconnects with the bed and there is deformation (Phase 2). As temperatures and meltwater decline in the afternoon/evening, velocities are at their slowest and deformation is low (Phase 3), and then as temperatures begin to warm the next morning, the glacier begins to speed up and deformation increases (Phase 4). In winter, there is a similar multi-day pattern associated with meltwater from the winter events. The sliding phase is accompanied by a decline in water pressure and antithetic (backwards) change in tilt associated with unloading 55 , 56 (Phase A). The reconnection phase has very high synthetic tilt (Phase B), and then there is a period of stick with no tilt movement as water pressures fall below that able to produce deformation (Phase C). Finally, there is a final phase of increasing water pressures and synthetic tilt movement (Phase D). We can extend this interpretation to the other glaciers in the study (see Methods) and based on these observations, it was possible to calculate the amount of time that these processes occur in both summer and winter, and for the whole year. We can divide the time into three main states: i) sliding (Phase 1 & A); ii) deformation (Phases 2–4 & B, D); and iii) no deformation (Phase C). In this way we have a quantification of subglacial processes (Table 3 ). Table 3 – Calculation of different time periods for subglacial processes Stage Skálafellsjökull # Fjallsjökull Breiðamerkurjökull Briksdalsbreen Melt season % Winter % Whole year % Melt season % Winter % Whole year % Melt season % Winter % Whole year % Melt season % Winter % Whole year % 1/A –Sliding associated with the speed-up event 18 9 13 17 11 14 29 10 19 15 6 12 2/B- Deformation associated with reconnection as glacier slows down 51 10 30 46 28 36 33 32 32 35 13 27 3 Low deformation associated with velocity minimum 17 26 13 23 13 17 28 41 C Stick 35 33 21 67 4/D- Deformation associated with reactivation as glacier begins to speed up 14 46 31 25 28 27 25 37 31 22 14 19 Annual Sliding 13 14 19 12 Deformation 69 69 70 65 No deformation 18 17 11 23 # The value is different to that previously quoted 27 as those only included one year, whilst the figure above is a mean of two years. The pattern at Fjallsjökull was very similar to Skálafellsjökull. However, at Breiðamerkurjökull, during summer there is double diurnal velocity peak and in winter 81% of the winter events were accompanied by more than one sliding event, many of which were not related to weather conditions, whilst 55% of cycles did not have a sliding phase at the beginning, and there was a lag before sliding occurred. At Briksdalsbreen the pattern in the melt season was similar to Skálafellsjökull, but in winter there were two speed-up events during each winter event. The first is associated with the build-up of porewater pressure due to the restriction of water moving through the till. The second is due to melt water production associated with rising temperatures. In this way Briksdalsbreen has two sliding episodes in each winter event, but the number of events per year is very low, so there is only 4% sliding during the winter. Overall, our study glaciers have a relatively similar pattern but with some small differences. For those glaciers associated with a braided system (Skálafellsjökull and Fjallsjökull) sliding represents 13–14% of the year, deformation 69% of the year, with no deformation occurring 17–18% of the year; whilst at those associated with a channelized system (Briksdalsbreen) there are similar levels of sliding (12%) slightly lower deformation (65%) and slightly higher periods of no deformation (23%). However, this overall pattern includes seasonal differences: in the channelised system sliding was high in summer, but very low in winter. In the intermediate system (Breiðamerkurjökull) there is slightly higher annual sliding (19%), similar deformation (70%) and shorter periods of no deformation (11%). Much of this variation is due to the higher levels of sliding during the melt season related to the double velocity peaks. In winter, although there were fewer and slower speed-up events related to the winter events there were numerous non-weather-related events which we have suggested were due to calving. We have proposed that the different subglacial hydrology’s are associated with different subglacial processes. This may be useful in reconstructing the rate and nature of processes associated with Quaternary tills. Sliding may be associated with lodgement till 27 , whilst the deformation recorded at our sites will a result in deformation till 31 , 57 , 7 . Glacio-fluvial elements within tills may also be important indicators. Classically eskers are associated with channelized drainage 58 , whilst the sedimentary remains of ‘canals’, ‘subglacial meltwater corridors’ and murtoos 52 , 59 , 60 , 61 may reflect the braided system. Stratified lenses within till are common and have been given numerous interpretations, either reflecting preglacial outwash that have been incorporated into the till, usually by attenuation and boudinage 62 or penecontemporaneous sedimentation with the till either in a braided system 63 , 64 or at the ice sediment interface 67 , 66 . These are very often subsequently deformed as they are deposited associated with a deforming bed. Our study highlights that we would expect to find sedimentary evidence for a braided system in subglacial tills, and these would very likely be deformed given the high duration of deformation associated with a braided system (Fig. 6 ). Understanding subglacial behaviour is a key element in understand glacier response to climate change and global sea level prediction. We have proposed a unique methodology to identify subglacial hydrology from Sentinel-1 SAR imagery, supported by Glacsweb in situ probe and daily GPS data. This hypothesis has the potential to enable the subglacial regime of numerous glaciers to be identified, and in particular test the relative occurrence of different subglacial hydrological systems associated with soft-bedded glaciers worldwide. We have also discussed the different subglacial processes associated with these different subglacial hydrological systems. This model now needs to be tested at other locations, and the detailed glaciological effects of these different hydrological systems examined. Methods Environmental Sensor Network and the Glacsweb in-situ wireless probes An environmental sensor network system was designed to collect the in-situ probe data, comprising sensor nodes and base stations, which are linked together by radio networks. Data was recorded from the probes at Briksdalsbreen (2004–2006) every four hours and at Skálafellsjökull initially every hour (2008–2010), and then every 15 minutes during 2012. Their data was transmitted from base stations via GPRS to a cloud server and hence to a sensor network server in the UK. Node data, along with differential GPS (dGPS) recordings and meteorological data, were sent once a day to a mains powered computer (5 km at Briksdalsbreen, 16 km Skálafellsjökull), where it was forwarded to a web server in the UK 34 , 27 . The specific site location on the glacier was determined by the optimal depth at which the system can transmit data through the till and ice (50–80 m). These probes were deployed in the summers of 2004, 2005, 2008 and 2012, in a series of boreholes, which were drilled with a Kärcher HDS1000DE jet wash system. Once the boreholes were made, the glacier and till were examined using a custom-made CCD colour video camera with infrared LED illumination. If till was present it was hydraulically excavated 67 by maintaining the jet at the bottom of the borehole for an extended period of time. The probes were then lowered into this space, enabling the till to subsequently close in around them. The depth of the probes (in the till) was estimated from video footage of the ice/till interface to be ~ 0.1–0.3 m at Briksdalsbreen and ~ 0.1 − 0.2 m at Skálafellsjökull beneath the glacier base. These water pressure data were calibrated against the measured water depths in the borehole immediately after probe deployment. The glacier thickness ( H ) was determined from measuring the depth of the boreholes and comparing with the GPS data of the glacier surface. Effective pressure N is calculated as follows: N = P i -P w where P i = pressure of ice, and Pw = water pressure. Pi = p i gH Where p i = density of ice (910 kg m − 3 ), g = gravity (9.8 m s − 2 ) and H = ice thickness. In addition, custom-made, low-power geophones were installed within boreholes to avoid surface seismic noise. The geophone nodes continually sampled the output of three orthogonal geophones but only data from seismic events were stored, held temporarily on a micro-SD card until they were retrieved by the base station. We used a 25 dB amplifier to provide sufficient signal with a bandpass pre-filter of 0.5–234 Hz, and a sampling rate of 512 Hz 35 . Internet of Things Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS) We designed and built a unique low-cost, internet connected (with real-time solutions) GNSS with which to measure movement in remote locations. This was installed at Fjallsjökull and Breiðamerkurjökull (2017–2020). The system comprises a base station, one or more rovers and a server receiving the data. It was based on L1/L2 dGPS from Swift Navigation (Piksi Multi), which use 3W when operating, providing a typical accuracy of 2 cm after 40s fix time and receive corrections from GPS, GLONASS and Galileo satellites. They are only powered on when taking readings to save battery lifetime. The system was controlled by an ARM M4 microcontroller (96 kB RAM, 384 kB flash), which has a sleep current of 6 µA and ran micropython. Synchronised base station units were placed in the foreland, which transmitted the dGPS corrections to the rovers according to the schedule. An Iridium short messaging unit (Rockblock) was used by the rovers to send 8 readings once per day (330 bytes) directly to our database, allowing daily updates of data interpretation. The annual data were collected by Version 1 of the system which operated 2017–2020. The data shown is from Fjallsjökull, located where the ice was ~ 77 m deep, and Breiðamerkurjökull where the ice was 84 m thick. The summer diurnal data were collected from Version 2 of the system installed in 2024, which was installed in a similar location. Velocity records Ice surface velocity was measured at Skálafellsjökull from 2008–2012 with a TOPCON Legacy-H L1/L2 GPS (1 km baseline), and from 2012–2013 with an additional array of 4 dual frequency Leica 1200 GPS systems which obtained data continuously during the summer and 2 h a day during the winter at a 15 s sampling rate (300 m baseline). The GPS data were then processed using data from the International GPS Service (IGS) reference stations using TRACK (v. 1.24), the kinematic software package developed by Massachusetts Institute of Technology (MIT) http://geoweb.mit.edu/~tah/track_example/ ). We derived an average surface horizontal velocity by taking the mean of 4 GPS stations to remove local variations. To account for surface melting, we removed the daily melt from the vertical measurements. The mean error estimates were as follows (sigma per day): North +/− 0.0045 m, east +/− 0.0032 m, height +/− 0.0092 m. We have previously demonstrated 16 that velocity has a distinct pattern related to air temperature and utilised a transfer function to reconstruct a velocity record for 2009/10 using the velocity data from 2012/13. At Fjallsjökull and Breiðamerkurjökull, the surface velocity was measured with the web connected RTK GNSS system discussed above. The error estimates were +/- 2 cm. Sentinel-1 SAR imagery was also used to calculate glacier-wide velocities at 12-day repeat intervals. Data were generated using the offset tracking algorithm within the European Space Agency (ESA) Sentinel Application Platform (SNAP). Although offset tracking is less precise than SAR interferometry, given the high temporal correlation of glacier surfaces, it is much more robust, and as such the method is widely used in glacier motion assessment 70 . Here, each pair of SAR images were first calibrated and then co-registered using the aerial LiDAR DEM of Iceland, provided at 10 m resolution by the National Land Survey of Iceland. Velocities were then calculated using cross correlation, with specific parameters, including the moving window size and search distance, varying between each glacier (Table 5 ). Table 5 Processing parameters used in SNAP to produce velocity rasters of each glacier. Glacier Grid Azimuth Spacing (pixels) Grid Range Spacing (pixels) Registration Window Width/Height Max. Velocity (m d − 1 ) Skálafellsjökull 5 5 64 x 64 1.5 Breiðamerkurjökull 20 20 256 x 256 5 Fjallsjökull 10 10 128 x 128 4 Briksdalsbreen 15 15 64 x 64 2 Any displacements with a cross-correlation threshold of < 0.01 were then removed, with the remaining displacements averaged over a mean pixel grid and converted to ground range coordinates, resulting in velocity rasters at 10 m resolution. The stochastic error in our velocity measurements was assessed by measuring displacements over terrain that we regarded as stable 71,72 .The average RMSE for the Sentinel-1 imagery over the entire period was +/−0.15 m per day. This was calculated from June 2017 to Oct 2020. Mean velocities and errors were then calculated along the centre line of the glaciers. We calculated the change in 12-day velocity over the summer by comparing the maximum velocity during the spring with the lowest velocity just prior to the autumn velocity rise, which we express as a percentage. We do this for each year, taking a mean for each glacier. Air temperature records, defining the seasons and determining the relationship between winter events and velocity change Air temperature data were primarily obtained from the base stations described above but during periods of mechanical failure, a transfer function was applied to data from neighbouring meteorological stations. For Skálafellsjökull we used Hofn (~ 30 km away), for Fjallsjökull and Breiðamerkurjökull we used Kvisker (~ 6 and ~ 16 km away respectively) and for Briksdalsbreen we used Stryn (~ 30 km away). We define the seasons based on air temperatures, and since the sites have different mean annual temperatures (Table 1 ) we utilised slightly different seasonal thresholds. Winter is a time where there is little melting as temperatures are low. We have used the mean annual air temperature as this threshold (Skálafellsjökull 0 o C, Fjallsjökull and Breiðamerkurjökull 5 o C, and Briksdalsbreen 6 o C). Spring begins once the daily temperatures are continuously above the winter threshold, summer is reflected by much higher temperatures (~ 5 O C higher than the winter threshold), autumn temperatures are lower often falling below zero at night. We quantified the glacier response to the winter events in two ways. For the daily velocity data from GPS, we counted the percentage of events where the speed-up event occurred at the same time as a temperature rise above the threshold. For the 12-day velocity data from Sentinel-1, we calculated the number of days within each period that air temperatures were above the threshold (N). We assumed that if the value of N was zero, it would reflect a base (low) velocity, it if were above zero it would reflect a speed-up event (high velocity). We then calculated the percentage of ‘correct’ attributions over the winter. We set the threshold between low and high velocity at 95% of the winter velocity. Determining the different phases of stick-slip motion The initial determination of the different phases of stick-slip motion were calculated from the tilt, geophone, velocity and air temperature data from Skálafellsjökull. There are four phases (diurnal in melt season indicated by a number, multi-day in winter by a letter): sliding (Phase 1/A), reconnection (Phase 2/B), low or no deformation (Phase 3/C), reactivation (Phase 4/D). We were able to extend this analysis to the other glaciers in the study. At Fjallsjökull and Breiðamerkurjökull, although we do not have tilt or geophone data, the data from Skálafellsjökull clearly illustrate a relationship between tilt and velocity, so that velocity can be used as proxy for tilt in the analyses. Although the velocities from Skálafellsjökull were very similar during Stages C and D, they could be distinguished using air temperature: Stage C occurred when temperatures were low (below zero), whilst Stage D was associated with rising temperatures (just before the threshold for the winter event to occur). This enabled us to isolate the two stages at Fjallsjökull and Breiðamerkurjökull: Stage C was associated with low velocity and low air temperatures (less than 5°C), and Stage D with rising air temperatures (and occasionally higher velocity). At Briksdalsbreen, where tilt data was available but not velocity, it was possible to use these alongside air temperatures to identify the different phases. During the melt season, there was a distinct daily pattern. As air temperatures (and presumably velocities) rise in the morning they are accompanied at midday by low tilt change, which we suggest reflects sliding (Phase 1). During the afternoon, there was an increase in tilt change, which we suggest reflects reconnection with the bed (Phase 2) and deformation throughout the afternoon and evening. Tilt motion/deformation is then lowest at midnight (Phase 3), before increasing slightly throughout the morning as the glaciers speeds up in response to increasing melt (Phase 4). During winter, there was also a pattern of stick-slip motion but with a more complex, double configuration. When temperatures drop below zero, water pressures rise, until a water pressure threshold is crossed (after ~ four days), and we assume there is a speed-up event that generates the antithetic behaviour and sliding (Phase A) (Fig. 4a, DOY 23). After this the glacier slows down and reconnects with the bed, resulting in deformation (indicated by the large synthetic tilt movement) (Phase B) (Fig. 4a, DOY 24). If the water pressure is sufficiently high then there will not be a stick phase, but rather continuous low synthetic deformation. This is often indistinguishable from the reconnection Stage D (Fig. 4a, DOY 25–34) so we have grouped the two together. Then as air temperatures again rise above zero we see a pattern similar to Skálafellsjökull. Firstly, meltwater enters the system, resulting in sliding and antithetic deformation (Phase A) (Fig. 4a, DOY 35), then a dramatic decline in water pressure associated with synthetic tilt (Phase B) (Fig. 4a, DOY 36), followed by a period of stick (Phase C) (seen in event 1) or low deformation (Phase D) (Fig. 4a, DOY 37–42) (seen in the rest of the events) depending on porewater pressures. Declarations Data Availability Data is available at Glacsweb.org ( https://data.glacsweb.info/datasets/ ) and a DOI will be provided on publication. Acknowledgements The authors would like to thank the Glacsweb 2003-2024 teams for help with probe development and data collection. They would also like to thank Matthew Roberts of the Icelandic Meteorological office for his advice and support. We would also like to thank Dr Phillip Basford and Josh Curry and for help with design of the Smart tracker and database. The authors also thank Eyjólfur Magnússon for sharing his bedrock topography data for Fjallsjökull. This research was funded by EPSRC (EP/C511050/1), Leverhulme (F/00180/AK, RPG-2021-316) and the National Geographic (GEFNE45-12, NGS-368R-18) and the GPR and Leica 1200 GPS units were loaned from the NERC Geophysical Equipment Facility. Contributions J.K.H. and K.M. designed the study. J.K.H. carried out the probe, discharge and GNSS data analysis. K.M. and G.B. designed the sensor network system, Glacsweb probes and web connected GNSS system as well as the software. N.R.B., B.A.R., A.B derived the remotely sensed surface velocity. J.K.H. wrote the manuscript with input from all authors. Competing interests The authors declare no competing interests. References Zemp, M., Huss, M., Thibert, E., Eckert, N., McNabb, R., Huber, J., Barandun, M., Machguth, H., Nussbaumer, S.U., Gärtner-Roer, I. & Thomson, L. 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Upper-flow regime bedforms in a subglacial triangular-shaped landform (murtoo), late Pleistocene, SW Finland: Implications for flow dynamics and sediment transport in (semi-) distributed subglacial meltwater drainage systems. Sedimentary Geology , p.106448 (2023). Hart, J. K. & Boulton, G. S. The interrelation of glaciotectonic and glaciodepositional processes within the glacial environment. Quaternary Science Reviews 10(4), 335–350 (1991). Evans, D.J., Owen, L.A. & Roberts, D., Stratigraphy and sedimentology of Devensian (Dimlington Stadial) glacial deposits, east Yorkshire, England. Journal of Quaternary Science 10(3), 241–265 (1995). Hart, J. K. Subglacial deformation associated with a rigid bed environment, Aberdaron, North Wales. Journal of Glacial Geology and Geomorphology 1 (1), 1–18 (1996). Piotrowski, J. A. & Tulaczyk, S. Subglacial conditions under the last ice sheet in northwest Germany: ice-bed separation and enhanced basal sliding? Quaternary Science Reviews 18(6), 737–751 (1999). Clerc, S., Buoncristiani, J. F., Guiraud, M., Desaubliaux, G. & Portier, E. Depositional model in subglacial cavities, Killiney Bay, Ireland. Interactions between sedimentation, deformation and glacial dynamics. Quaternary Science Reviews 33, 142–164 (2012). Blake, E.W., Clarke, G.K.C. & Gerrin, M.C. Tools for examining subglacial bed deformation. Journal of Glaciology 38, 388–396 (1992). Nagler, T., Rott, H., Hetzenecker, M., Wuite, J. and Potin, P. The Sentinel-1 mission: New opportunities for ice sheet observations. Remote Sensing , 7(7), 9371–9389 (2015). Robson, B.A., Nuth, C., Nielsen, P.R., Girod, L., Hendrickx, M. & Dahl, S.O. Spatial variability in patterns of glacier change across the Manaslu Range, Central Himalaya. Frontiers in Earth Science 6, 1–12 (2018). Baurley, N.R., Robson, B., & Hart, J.K. Long-term impact of the proglacial lake Jökulsárlón on the flow velocity and stability of Breiðamerkurjökull glacier, Iceland. Earth Surface Processes and Landforms 45 (11), 2647–2663 (2020). Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Published Journal Publication published 21 Mar, 2025 Read the published version in Communications Earth & Environment → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4539760","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":313186182,"identity":"06a39f75-ac36-4cf2-a033-18a41cf78fdc","order_by":0,"name":"Jane Hart","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwUlEQVRIiWNgGAWjYBACxhkgsgJJRIIoLQfOMDDwEK0FrOJgGylamGc3P/v8cV6dnD177wGGHzUMiTMbCDlszjHjGQe3HTbm4TmXwNhzjCFxNiFbGGckGDMc3HYgsUcix4CBt4EhcR5hLemfGQ7OqQNrYfxLnJYcoC0NzGAtzCBbiHBYTjHDmWNAv5w5Y3BY5piEMUHvG85I38xQUVMnx97eY/jwTY2N7IwDhLQgm3mAmIhkkCesZBSMglEwCkY8AAB7Pj4u5I6KHQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-2348-3944","institution":"University of Southampton","correspondingAuthor":true,"prefix":"","firstName":"Jane","middleName":"","lastName":"Hart","suffix":""},{"id":313186183,"identity":"a0691e5c-befe-480a-9816-dd6622604ae3","order_by":1,"name":"Nathaniel Baurley","email":"","orcid":"","institution":"University of Southampoton","correspondingAuthor":false,"prefix":"","firstName":"Nathaniel","middleName":"","lastName":"Baurley","suffix":""},{"id":313186184,"identity":"7f53c0d1-fa7d-4987-bccd-aebc683891b8","order_by":2,"name":"Amy Bonnie","email":"","orcid":"","institution":"University of Southampoton","correspondingAuthor":false,"prefix":"","firstName":"Amy","middleName":"","lastName":"Bonnie","suffix":""},{"id":313186185,"identity":"a4489708-a0f9-41af-9731-49ad2de647e9","order_by":3,"name":"Benjamin Robson","email":"","orcid":"","institution":"University of Bergen","correspondingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Robson","suffix":""},{"id":313186186,"identity":"7bdfb3fc-001d-4d92-a2a6-5d711c06ded4","order_by":4,"name":"Graeme Bragg","email":"","orcid":"","institution":"University of Southampton","correspondingAuthor":false,"prefix":"","firstName":"Graeme","middleName":"","lastName":"Bragg","suffix":""},{"id":313186187,"identity":"355c6d20-2020-42e1-811b-673b0bcd48c2","order_by":5,"name":"Kirk Martinez","email":"","orcid":"","institution":"University of Southampton","correspondingAuthor":false,"prefix":"","firstName":"Kirk","middleName":"","lastName":"Martinez","suffix":""}],"badges":[],"createdAt":"2024-06-06 10:50:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4539760/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4539760/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s43247-025-02198-0","type":"published","date":"2025-03-21T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59593598,"identity":"0f12001f-c6e4-4308-b7de-726d6d08d98b","added_by":"auto","created_at":"2024-07-03 15:18:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1197986,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eField sites: a) overall location; b) Fjallsjökull, Breiðamerkurjökull and Skálafellsjökull, Iceland; c) Briksdalsbreen, Norway (Source: Esri, Maxar, GeoEye, Earthstar, Geographics, CNES/Airbus DA, USDA, AreoGRID, IGN and the GIS User Community).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4539760/v1/0caa6037d33c278b51444c32.png"},{"id":59593592,"identity":"6423d0a0-54bb-411d-ba88-b166cd08361a","added_by":"auto","created_at":"2024-07-03 15:18:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":233676,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAnnual pattern of behaviour (water pressure, daily velocity, air temperature)from each glacier: a) Skálafellsjökull, Probe S21 and S25, 2009/10; b) Fjallsjökull (upper) and Breiðamerkurjökull (lower), daily velocity 2017/18; c) Briksdalsbreen, Probe B8 (solid line) and air temperature 2004/5 and B12 (dotted line) from 2005/6 (all data plotted from 1\u003c/em\u003e\u003csup\u003e\u003cem\u003est\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e September).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4539760/v1/42aadf73255c004d14833841.png"},{"id":59594131,"identity":"f5a603df-8081-427e-be32-4cd5966524b7","added_by":"auto","created_at":"2024-07-03 15:26:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":172452,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAnnual pattern of 12-day remotely sensed velocity data (shown as a horizontal bar) plotted against daily air temperature 2018/19: a) Skálafellsjökull; b) Fjallsjökull \u0026amp; Breiðamerkurjökull; c) Briksdalsbreen (velocity data from Nigardsbreen) (all data plotted from 1\u003c/em\u003e\u003csup\u003e\u003cem\u003est\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e September).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4539760/v1/e91eff1d96d082e2d8ae3375.png"},{"id":59593594,"identity":"89e15184-78f2-4cac-94b5-f3790fc3ddd0","added_by":"auto","created_at":"2024-07-03 15:18:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":253130,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eExamples of winter events (left) and mean diurnal summer properties (right) from each galcier: a) Skálafellsjökull (DOY 309-314, 2012) (floatation pressure estimated from the behaviour during winter events during 2009); b) Skálafellsjökull summer 2012; c) Fjallsjökull (solid line) and Breiðamerkurjökull (dotted line) (DOY 319-330, 2018); d) Fjallsjökull and Breiðamerkurjökull summer 2023; e) Briksdalsbreen (DOY 19-40, 2004/5); f) Briksdalsbreen summer (probe B8) (DOY 211-248, 2004/5) (solid line), and mean autumn (DOY 249-320, 2005/6) (dotted line).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4539760/v1/88dcb34a5f83ca5b1bfcd85d.png"},{"id":59594130,"identity":"812685dd-80c0-4930-a9b1-634186a45f7d","added_by":"auto","created_at":"2024-07-03 15:26:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":194558,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eConceptual diagram to illustrate the seasonal subglacial drainage associated with soft-bedded glaciers: a) braided system, b) drained braided system, c) channelized system. The ‘ponds’ are representative of the larger subglacial reservoirs.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4539760/v1/5ea78edd9d751b1f72e9c0cc.png"},{"id":59593597,"identity":"47ab0019-4ebc-477a-b76e-e43bebf3c18c","added_by":"auto","created_at":"2024-07-03 15:18:18","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":692706,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTypical Quaternary examples of stratified lenses within deformation till from the Anglian till at West Runton, Norfolk, UK. These lenses represent either outwash sand deposition before the glacier advance and subsequently deformation or penecontemporaneous sedimentation and subsequent deformation within a braided system. Scale of sand lens in c equals 2.1 m x 1m, and in d equals 0.5 m x 0.3 m.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4539760/v1/3e762a34c2b0570f9159db89.png"},{"id":79004515,"identity":"1a456efb-5795-49ee-8492-061d5545710a","added_by":"auto","created_at":"2025-03-22 07:09:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4580867,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4539760/v1/bc2c9bed-e413-41fe-b175-2beb418f502f.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Seasonal velocity patterns and deforming bed processes associated with different subglacial drainage systems.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAs glaciers worldwide melt in response to climate change, it becomes increasingly vital to determine their present and future contribution to sea level rise\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. These higher temperatures will lead to increased melting of the glacier, generating additional meltwater which can flow to the glacier bed, but there is no linear relationship between surface melt and glacier response\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. This is because of numerous factors within the glacial system, but in particular the behaviour of water and till at the glacier base\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e which control the \u0026lsquo;slipperiness\u0026rsquo; of the glacier bed (sliding laws)\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e .\u003c/p\u003e \u003cp\u003eGlaciers can flow over either rigid or unconsolidated bedrock (soft- beds). It has been a longstanding assumption that the subglacial hydrology of rigid beds comprises a predominantly channelised drainage in the summer \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. In contrast, it has been suggested that soft-bedded glaciers have a distributed system, based on observations from Antarctic ice streams\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e and mountain glaciers\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In addition, recent research on rigid-bedded glaciers from Greenland, suggests that distributed drainage exists alongside channelized during the late summer\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, whilst simultaneously new examples of soft beds are being discovered across Greenland\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e and many glaciers worldwide rest on mixed bedrock. These observations highlight that the subglacial hydrology for all bed types is more complex than initially envisaged, and there is a need to identify different subglacial hydrologies to understand glacier behaviour.\u003c/p\u003e \u003cp\u003eMeltwater draining into the subglacial till changes the effective pressure (normal pressure minus water pressure) of the glacier. As effective pressures range from low to high, so behaviour changes from sliding, to deformation, to stick (no/little motion)\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. It has been shown by numerous researchers that glaciers move via stick-slip motion\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, due to tidal or meltwater processes\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. A study of Sk\u0026aacute;lafellsj\u0026ouml;kull, a temperate soft-bedded glacier\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, showed that stick-slip motion occurred on a daily scale during the melt season and on a multi-day scale in winter. This process comprises both sliding and deformation, with the authors able to calculate the percentage times that these processes occurred throughout the season.\u003c/p\u003e \u003cp\u003eIn light of the importance of the role of the sliding law parameters in sea level rise predictions\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, there have been a number of recent discussions of the sliding (basal friction) law\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, with a recent model\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e proposing a single law to describe behaviour for both rigid and soft beds. However, any sliding law needs to include changing bed conditions to enable realistic parameterization.\u003c/p\u003e \u003cp\u003eWe examine a series of soft-bedded glaciers in maritime locations and use a range of techniques to investigate their seasonal behaviour. We are able to show a continuum between braided/multichannel and channelized systems. We argue the dominant controls on this range are till grainsize and subaqueous processes. The braided system is characterised by dramatic speed-up events during warm days during winter (winter events), a delayed and slow spring event, relatively stable summer velocities, and peak velocities during autumn. This is because during summer an anastomosing system develops which can adapt to meltwater changes, promoting stable velocities and facilitating water storage. This water is released during the winter allowing winter speed-up events, with a period of recharge needed during spring.\u003c/p\u003e \u003cp\u003eIn contrast, the channelized system has few/no winter speed-up events, a fast-spring event at the beginning of spring, a declining velocity over the summer, and similar peak velocities during autumn. Within a channelized system, the connected area increases over the summer (reducing velocity), but has much lower storage, hence fewer winter events, and a dramatic spring event once temperatures and meltwater increase.\u003c/p\u003e \u003cp\u003eWe are also able to quantify subglacial processes and use these, alongside the hydrological findings, to understand till and glaciofluvial sedimentology. In addition, using the results from our multi-data stream analysis, we propose that it is possible to identify the subglacial hydrological systems from the analysis of Sentenal-1 data alone.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eField Sites\u003c/h2\u003e\n \u003cp\u003eWe report the results from four temperate soft-bedded glaciers in relatively mild maritime locations (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e), using field based and remotely sensed data. We have studied three adjacent glaciers from the Vatnaj\u0026ouml;kull ice cap, Iceland: Sk\u0026aacute;lafellsj\u0026ouml;kull\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, Fjallsj\u0026ouml;kull and Brei\u0026eth;amerkurj\u0026ouml;kull. All three calve into proglacial lakes, approximately 20m, 100m, and 300m deep respectively\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The fourth glacier is Briksdalsbreen, Norway; which is an outlet glacier of the Jostedalsbreen ice cap\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, and also calved into a 20m deep proglacial lake. The field study of Briksdalsbreen took place 2004-6, and since then the glacier has dramatically retreated onto a plateau, so we have derived the remotely sensed velocity from the nearby Nigardsbreen.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDetails about the sites are shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. All four glaciers rest on a till base and have a foreland geomorphology composed of flutes and push moraines, indicative of subglacial deformation\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Field data was collected via the Glacsweb environmental sensor network\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e which comprises sensor nodes that relay their data to a sensor network server in the UK. This included \u003cem\u003ein situ\u003c/em\u003e sensor nodes (Glacsweb probes) inserted into the till (0.16 m long) which contained micro-sensors measuring water pressure, probe deformation, resistance, tilt and probe temperature\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Here we discuss the water pressure results, measured in hydraulic head (m) and then compared with the water column height from the known glacier thickness (flotation pressure %). We also calculate the effective pressure N, which is the ice overburden pressure minus water pressure. The system also included geophones to measure ice-quakes\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Secondly, we designed and built a web connected real time kinematic GNSS which was part of an Internet of Things (IoT) system\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Details of sensors, readings, locations and errors are discussed elsewhere\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, and details of the data sets are outlined in the \u0026lsquo;Methods\u0026rsquo;.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab1\" style=\"width: 1003px;\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDetails about the four sites\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth style=\"width: 111px;\" rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eField Site\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 99px;\" rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eData period\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 124px;\" rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eMean annual air temp. (\u003csup\u003eo\u003c/sup\u003eC)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 87px;\" rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eGlacier area (km\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 115px;\" rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eAltitude of study site (m)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 25px;\" rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eGPR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 102.567px;\" rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eGlacsweb Probe data\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 169.433px;\" colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eVelocity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 112px;\" rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eTill mean Grain size (\u0026micro;m)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth style=\"width: 104.433px;\" align=\"left\"\u003e\n \u003cp\u003eGPS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth style=\"width: 65px;\" align=\"left\"\u003e\n \u003cp\u003eSentinel \u0026minus;\u0026thinsp;1\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\" align=\"left\"\u003e\n \u003cp\u003eSk\u0026aacute;lafellsj\u0026ouml;kull\u003c/p\u003e\n \u003cp\u003e64.251\u003csup\u003eo\u003c/sup\u003eN, 15.832\u003csup\u003eo\u003c/sup\u003eW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\" align=\"left\"\u003e\n \u003cp\u003e2008\u0026ndash;2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\" align=\"char\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\" align=\"left\"\u003e\n \u003cp\u003e~\u0026thinsp;100\u003csup\u003e28\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\" align=\"char\"\u003e\n \u003cp\u003e792\u003csup\u003e27\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\" align=\"left\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102.567px;\" align=\"left\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104.433px;\" align=\"left\"\u003e\n \u003cp\u003eLeica System 1200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\" align=\"left\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\" align=\"char\"\u003e\n \u003cp\u003e53\u003csup\u003e27\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\" align=\"left\"\u003e\n \u003cp\u003eFjallsj\u0026ouml;kull\u003c/p\u003e\n \u003cp\u003e64.011\u003csup\u003eo\u003c/sup\u003eN, 16.428\u003csup\u003eo\u003c/sup\u003eW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\" align=\"left\"\u003e\n \u003cp\u003e2017\u0026ndash;2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\" align=\"char\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\" align=\"left\"\u003e\n \u003cp\u003e~\u0026thinsp;45\u003csup\u003e28\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\" align=\"char\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\" align=\"left\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102.567px;\" align=\"left\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104.433px;\" align=\"left\"\u003e\n \u003cp\u003eWeb connected RTK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\" align=\"left\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\" align=\"char\"\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\" align=\"left\"\u003e\n \u003cp\u003eBrei\u0026eth;amerkurj\u0026ouml;kull\u003c/p\u003e\n \u003cp\u003e64.099\u003csup\u003eo\u003c/sup\u003eN, 16.324\u003csup\u003eo\u003c/sup\u003eW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\" align=\"left\"\u003e\n \u003cp\u003e2017\u0026ndash;2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\" align=\"char\"\u003e\n \u003cp\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\" align=\"left\"\u003e\n \u003cp\u003e~\u0026thinsp;900\u003csup\u003e37\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\" align=\"char\"\u003e\n \u003cp\u003e173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\" align=\"left\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102.567px;\" align=\"left\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104.433px;\" align=\"left\"\u003e\n \u003cp\u003eWeb connected RTK GPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\" align=\"left\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\" align=\"char\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\" align=\"left\"\u003e\n \u003cp\u003eBriksdalsbreen\u003c/p\u003e\n \u003cp\u003e61.663\u003csup\u003eo\u003c/sup\u003eN, 6.864\u003csup\u003eo\u003c/sup\u003eE\u003c/p\u003e\n \u003cp\u003e(Nigardsbreen\u003c/p\u003e\n \u003cp\u003e61.884\u003csup\u003eo\u003c/sup\u003eN, 7.193\u003csup\u003eo\u003c/sup\u003eE)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\" align=\"left\"\u003e\n \u003cp\u003e2004\u0026ndash;2006, 20172020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\" align=\"char\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003cp\u003e(1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\" align=\"left\"\u003e\n \u003cp\u003e~\u0026thinsp;15\u003csup\u003e31\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(~\u0026thinsp;48\u003csup\u003e38\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\" align=\"char\"\u003e\n \u003cp\u003e375\u003csup\u003e31\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25px;\" align=\"left\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102.567px;\" align=\"left\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104.433px;\" align=\"left\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\" align=\"left\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\" align=\"char\"\u003e\n \u003cp\u003e1600\u003csup\u003e31\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cem\u003e*Data from the site over the study period, taken from the local metrological station, corrected for altitude/local conditions from weather station on the base station.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows the annual pattern of air temperature, till water pressure, and daily velocity for each glacier (where available) plotted from 1st September (DOY 244) (2009/10 for Sk\u0026aacute;lafellsj\u0026ouml;kull, 2017/8 for Fjallsj\u0026ouml;kull and Brei\u0026eth;amerkurj\u0026ouml;kull, and 2004/5 for Briksdalsbreen) whilst the annual 12 day velocity data from Sentinel-1 SAR imagery for each glacier for 2018/19 is illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eWe have defined the seasons for the four glaciers based on air temperature, which is related to melt\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Since these glaciers are in different locations/altitudes the detailed thresholds are discussed in the Methods.\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003eSk\u0026aacute;lafellsj\u0026ouml;kull\u003c/h2\u003e\n \u003cp\u003eThe annual pattern of water pressure, effective pressure and velocities are shown in Figs. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea. Winter comprises two states. A base state with high till water pressure and low velocity, and speed-up events where water pressures dramatically decrease and velocities increase. These speed-up events occur every time the temperature rises above zero (83% of the time), 12-day velocity data, with an 84% correlation (see Methodology for details).\u003c/p\u003e\n \u003cp\u003eAlongside these events, it has been reported that there is a vertical rise of the glacier and high discharge\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, and a pattern of initial antithetic (backwards) tilt change and then synthetic (forwards) tilt change\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. During the spring there is also a velocity increase, but this is within the upper range of the winter event velocities. This speed-up occurs\u0026thinsp;~\u0026thinsp;17 days after the beginning of spring and is not related to a specific weather event. In summer, water pressures remain consistently high whereas velocities are high at the beginning of summer but gradually decrease across the summer period (24% reduction, 12-day data). In contrast, till water pressure slowly decreases during autumn, but velocity peaks are some of the highest. The effective pressures are low in the summer and high in the winter and have a very similar in pattern at each probe\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eFigure 4b illustrates the mean melt season diurnal tilt change, air temperature and velocity patterns. Air temperatures were lowest at 07:00, rising to a high plateau 12:00\u0026ndash;17:00, cooling rapidly until 21:00, then cooling more slowly until 07:00, with a small rise at 04:00. Velocities were also low in the morning, rising to a peak at 13:00, and then decreasing throughout the afternoon and evening, before a speed-up event at 4:00. The tilt-changes are generally low during the main high velocity event at midday, but high during slow down and speed-up period. These high tilt changes correlate with high ice quake events\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eResults from GPR studies\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e and net inputs and outputs\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e indicate that Sk\u0026aacute;lafellsj\u0026ouml;kull has a braided subglacial hydrology. During the summer, discharge only accounts for approximately 60% of inputs. The excess goes into the aquifer, the subglacial till, and the braided system itself in a series of backwater reservoirs. Water from the till and the reservoirs is partly released during winter, where discharge is 5 times larger than inputs.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eFjallsj\u0026ouml;kull\u003c/h2\u003e\n \u003cp\u003eThe annual velocity patterns are shown in Figs. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb. During winter there is a distinct base velocity, with speed-up events (~\u0026thinsp;6 times faster than the base), predominantly related to high air temperatures (temperatures\u0026thinsp;\u0026gt;\u0026thinsp;5\u003csup\u003eo\u003c/sup\u003eC), for both the daily (77% correlation) and 12-day (80% correlation) velocity. There is an average of 11 events per year, with an average length of 17 days. Detail of one of these events is illustrated in Fig.\u0026nbsp;4c.\u003c/p\u003e\n \u003cp\u003eThere were speed-up events\u0026thinsp;~\u0026thinsp;13 days after the beginning of spring (\u0026lsquo;spring event\u0026rsquo;), but these are similar to the smaller winter event speed-ups which mark the beginning of the melt season when velocities rise to a higher mean level. Summer velocities are relatively stable, with a slight decrease over the season (daily velocity 45%, 12-day velocity 7%). Velocities were also high during autumn, likely to be related to weather conditions.\u003c/p\u003e\n \u003cp\u003eThe mean summer diurnal pattern of velocity and air temperature is shown in Fig.\u0026nbsp;4d (mean of 2023 results). Air temperatures are lowest at 04:00, slowly rising throughout the morning to a high temperature plateau between 13:00\u0026ndash;15:00 and then decreasing overnight. At Fjallsj\u0026ouml;kull, the velocity was also lowest in the early morning (06:00), and rising to a peak at 15:00, and then decreasing overnight. The peak velocity occurred 1\u0026ndash;2 hours after peak air temperatures. Note the air temperature data is hourly whilst the velocity data is every 3 hours.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eBrei\u0026eth;amerkurj\u0026ouml;kull\u003c/h2\u003e\n \u003cp\u003eAt Brei\u0026eth;amerkurj\u0026ouml;kull there are fewer and relatively slower winter speed-up events (approx. three times faster than the base velocity), and many are unrelated to meteorological conditions. The correlation for the daily velocity and air temperature is only 61% and 58% for the daily and 12-day scale, respectively. When a speed-up event does occur in response to increased temperatures, it occurs almost immediately (Fig.\u0026nbsp;4c) and there are often other speed-up events within one winter event.\u003c/p\u003e\n \u003cp\u003eThere was a speed-up event at the beginning of spring associated with the rise in air temperatures, marking the beginning of the higher melt season velocities. This was recorded in the daily velocity from 2018, and occurred on the 8th May (DOY 128), which was equivalent to the 90% percentile of the winter events, followed by a much faster speed-up event on the 13th May (DOY 133) (140% larger than fastest winter event). This latter event occurred after five days of high temperatures and rainfall. In the 12-day data this occurred in the 8th -20th May period in 2018 (DOY 128\u0026ndash;140) (equal to maximum winter event velocities), 27th May-8th June period in 2019 (DOY 147\u0026ndash;159) (highest velocity of the year) and 9th -21st May period in 2020 (DOY 130\u0026ndash;142) (top 80% percentile of winter events). These all occurred once temperatures rose above the threshold. Summer velocities, meanwhile, are relatively stable, with a slight decrease (daily 34% and 12-day 4%), whilst autumn velocity patterns are intermediate between summer and winter.\u003c/p\u003e\n \u003cp\u003eAt Brei\u0026eth;amerkurj\u0026ouml;kull, the diurnal velocity pattern (mean summer 2023) was different to that observed at Fjallsj\u0026ouml;kull (Fig.\u0026nbsp;4d). The velocity had a double peak, rising during the afternoon to a peak at 18:00 (4 hours after peak temperature), then decreased during the evening before rising to a second peak during the night (03:00).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eBriksdalsbreen\u003c/h2\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ed shows the annual air temperature (2004/5) plotted against the till water pressure from two probes: B8 (2004/5) and B12 (2005/6). The \u003cem\u003ein-situ\u003c/em\u003e tilt data from these probes\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e was used to investigate subglacial processes. Although a TOPCON GPS system was installed at the site, the data was only resolved at a monthly scale and so is not used here. The field study took place before Sentinel-1 was launched, so there are no available satellite images of the glacier from 2004/5 with which to calculate velocity at a comparable temporal resolution. In light of this, we utilise Sentinel-1 velocity analysis of the nearby Nigardsbreen glacier, as it is of a similar size, altitudinal range and aspect to Briksdalsbreen during the early 2000\u0026rsquo;s.\u003c/p\u003e\n \u003cp\u003eDuring the winter, the till water pressure was approximately zero for probe B12, whilst at B8 it was generally low, except for a series of dramatic increases that occur when the air temperature declines below zero. There were four events during 2004/5 (DOY 321\u0026ndash;352, DOY 353\u0026thinsp;\u0026minus;\u0026thinsp;18, DOY 19\u0026ndash;42, and DOY 43\u0026ndash;80), with details of one of these events illustrated in Fig.\u0026nbsp;4e. Initially, there was a period where temperatures were below zero, followed by a phase of above-zero temperatures. Once temperatures fell below zero, there was a mean four-day lag before water pressures increased. This was accompanied by an antithetic (backwards) tilt movement lasting one day and then a large synthetic (forward) tilt movement also lasting one day, followed by a period (mean length 16 days) of low synthetic tilt during the sub-zero temperatures. Once temperatures rose above zero, water pressure rapidly declined, and there was a repeat pattern of one day antithetic tilt followed by one day of synthetic tilt. After this, there was a long period (mean length 18 days) when the water pressures were low, with low synthetic tilt.\u003c/p\u003e\n \u003cp\u003eDuring the spring, water pressures rise as air temperatures increase. For probe B8 the rise is relatively slow (2.9 m floatation pressure % per day), whilst at B12 there is a double event. A one-day dramatic rise and fall on DOY 68, followed by an abrupt rise on DOY 86 (36 m flotation pressure % per day) which marks the Spring event. A similar pattern was also seen at probe B10 (not shown here but reported elsewhere\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e), which showed a double peak but with different timings (initial rise and fall DOY 106, main abrupt rise DOY 117). Summer begins with high pressures (~\u0026thinsp;DOY 111\u0026ndash;175), which slowly decrease in mid-summer (~\u0026thinsp;DOY 176\u0026ndash;223), then rapidly decrease in late summer (~\u0026thinsp;DOY 224\u0026ndash;240). During the autumn (DOY 241\u0026ndash;320), till water pressures are either high (B12) or zero (B8).\u003c/p\u003e\n \u003cp\u003eThe effective pressure has a distinct record. In summer probe 8 the water pressure exceeds the local overburden pressure (negative effective pressure) known as excess water pressure. Whilst for probe 12 the effectives pressures are low (but positive) in the summer but are over pressurized in autumn. During winter, in each probe, effective pressures are high.\u003c/p\u003e\n \u003cp\u003eFigure 4f shows the mean summer mean air temperature and tilt. Air temperatures rise in the morning (04:00 to 12:00), peak in the afternoon (12:00 to 16:00) and then decline overnight (16:00\u0026ndash;04:00). The tilt change pattern shows least movement in the night (04:00), slowly rising in the morning (04:00\u0026ndash;12:00), peaking at 16:00, and then falling. The autumn tilt changes from probe 12 show a similar pattern, but with more extreme changes, with a secondary peak in tilt during the early morning (04:00).\u003c/p\u003e\n \u003cp\u003eIn winter, the 12-day velocity data (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ed) varies throughout the season but only has a low, 54%, correlation with temperature data. In spring, there is a fast speed-up event equal to or greater than the winter events, which occur during the first 12-day period of spring each year. Velocities tend to decrease over the summer (38%) and rise again in autumn.\u003c/p\u003e\n \u003cp\u003ePrevious results from GPR studies\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e indicate that Briksdalsbreen has a channelized subglacial hydrology.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe growing recognition of braided/multichannel river systems associated with soft-bedded glaciers in Antarctica\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e could lead to a possible assumption that all soft-bedded glaciers have such a system. However, we have demonstrated here that this is not the case, and that there is likely a continuum between a distributed and a channelized system (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). We will now discuss the different seasonal behaviours associated with this continuum, suggest some controlling factors, outline how it is possible to identify the separate regimes based on velocity records, and quantify and identify different subglacial sedimentary processes.\u003c/p\u003e\n\u003cp\u003eThe results from Sk\u0026aacute;lafellsj\u0026ouml;kull provide evidence of the seasonal development of a braided river system associated with a soft-bedded glacier (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea). During the summer, the level of anastomosing is related to melt, and large parts of the bed have high connectivity. At the beginning of summer, as the channels are opening, melt increases lead to velocity increases. However, later in summer, the high levels of melt results in enhanced anastomosing, with a resultant velocity decline. Whenever the melt exceeds the carrying capacity of the system, this leads to reduced effective pressure and summer speed-up events\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e .\u003c/p\u003e\n\u003cp\u003eDuring autumn meltwater inputs decrease, meaning the level of anastomosing also decreases, as well as the connectivity, with water flow concentrated along the main channels. As a result, water may become isolated in backwater elements (\u0026lsquo;ponds\u0026rsquo;), whilst it will also drain out of the till resulting in decreased water pressures. High meltwater inputs at this time result in the fastest peak velocities because in this transitional state the subglacial system is easily overwhelmed\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eDuring winter, as there is little meltwater generated, there is low flow through the main channels and the till, resulting in low velocities. However, during winter events there are speed-up events with shear-induced till dilation\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, glacier uplift and high discharge. Water is released from the subglacial reservoirs, which include the till, cavities, macroporous sources and the ponds. These become \u0026lsquo;connected\u0026rsquo;, and water is able to flow at the ice/till interface into the main channels.\u003c/p\u003e\n\u003cp\u003eDuring spring the meltwater input increases, being accommodated within the main winter channels whilst connectivity within the till increases, until a threshold is passed (after ~\u0026thinsp;17 days), and then a speed-up (spring) event occurs. Afterwards, the system adapts to the new higher melt levels associated with summer via the anatomising of the channels.\u003c/p\u003e\n\u003cp\u003eThe pattern of behaviour at Fjallsj\u0026ouml;kull was very similar to that at Sk\u0026aacute;lafellsj\u0026ouml;kull, with the winter speed-up events, a non-weather-related spring event occurring\u0026thinsp;~\u0026thinsp;13 days after the beginning of spring, relatively stable summer velocities, and high autumn velocities. Because of this, we suggest that this also has a braided river system.\u003c/p\u003e\n\u003cp\u003eBrei\u0026eth;amerkurj\u0026ouml;kull is adjacent to Fjallsj\u0026ouml;kull with similar weather and bedrock conditions and thus would be expected to have comparable glacier behaviour. However, there are several key differences. This includes a lack of winter events and a distinct spring event related to weather conditions, a dual peak in summer diurnal temperatures (9 hours apart), whilst there are also numerous small speed-up events unrelated to weather conditions that occur during both summer and winter. We suggest that the difference in response is due to the presence of the deep proglacial lake J\u0026ouml;kuls\u0026aacute;rl\u0026oacute;n at Brei\u0026eth;amerkurj\u0026ouml;kull. It has been shown that deep lakes generate high hydrostatic pressure which leads to lake water being pushed up-glacier into subglacial channels\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. At the same time, high summer temperatures and rainfall will generate high discharge. Towards the margin, the bed could become over pressurised to enable the meltwater to be evacuated from the glacier. We suggest that the braided system switches to a more effective channelised system when meltwater input is high, releasing the excess melt water in short bursts. This allows any summer excess meltwater to be drained into the lake rather than be stored with the subglacial system. In addition, calving associated with the interactions between the glacier margin and the proglacial lake may help explain the non-weather-related speed-up events\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Increased velocity would encourage crevassing, allowing additional meltwater to reach the bed, as well as increasing the buoyancy of the glacier margin.\u003c/p\u003e\n\u003cp\u003eAlthough J\u0026ouml;kuls\u0026aacute;rl\u0026oacute;n has a tidal influence with two high tides a day\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, which could potentially affect the glacier, it would be expected for these to occur 12 hours apart, but even out over the season as the timings of tidal peaks change each day. As such, we suggest the dual peaks recorded in the summer diurnal pattern likely reflect the dominance of two water pathways. There is an initial velocity increase associated with midday melting, but much of the water is prevented from draining due to high hydrostatic pressures from the lake. This excess water builds up during the night until a threshold is passed, after which channelized drainage dominates.\u003c/p\u003e\n\u003cp\u003eWe suggest the following seasonal pattern (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eb): During summer there is a braided river system, but when melt is high, channelization occurs, which also drains any storage. In autumn, the anatomising decreases to a few main channels. During winter, these channels continue to shrink, but due to the lack of storage during times of melt, there is limited glacier response in terms of speed-up events. During spring the anastomosing increases, but the presence of high melt associated with warming causes a dramatic spring event, which cause the subglacial system to be overwhelmed.\u003c/p\u003e\n\u003cp\u003eIn contrast, Briksdalsbreen reflects typical channelized behaviour (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ec), with the till water pressure data indicating two distinct regimes within the system. The results from probe B8 reflect \u0026lsquo;highly connected\u0026rsquo; behaviour from a site close to the main channel (Type A) whilst those from B12 reflect \u0026lsquo;weakly connected\u0026rsquo; behaviour away from the main channel (Type B).\u003c/p\u003e\n\u003cp\u003eAt the beginning of summer (for both Type A and B behaviour), the water pressure is high, however, as the summer progresses till water pressures slowly decrease. There are high velocities at the beginning of summer, followed by a velocity decline as the summer progresses. This is similar to the pattern described from Greenland, where in early summer, meltwater is able to lubricate the bed, resulting in basal sliding\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, whilst later in summer, this meltwater can be accommodated by the subglacial system via the growth of the \u0026lsquo;weakly connected\u0026rsquo; distributed drainage\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e so velocities are reduced\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAs autumn approaches, close to the main channels, the till water pressure drops as these channels reduce in size in response to reduced meltwater inputs. However further away from these channels, the decrease in water pressure is slower as the system takes longer to adapt. Once autumn is established, any warm day will result in dramatic increases in velocity as the system is easily overwhelmed by meltwater inputs. Close to the main channels these high meltwater inputs drain into the channels and connected till, but away from the main channels these water inputs cannot easily drain, and so till water pressures rise.\u003c/p\u003e\n\u003cp\u003eDuring winter, temperatures remain above zero, so a small amount of water is generated by melt, as well as heat from glacier movement, and so the conduits remain open, although with much lower discharge. This results in low till water pressures, although some of this meltwater can drain through the till into the main channels. However, when temperatures are sub-zero, melt decreases, and the conduits begin to close. This means sites close to the main channel have their drainage restricted and water pressures rise, whilst those further away do not change, as any change in melt is distributed evenly through the till.\u003c/p\u003e\n\u003cp\u003eDuring spring, the area surrounding the main channel slowly adjusts to the increase in water input associated with spring melt (Type A), as parts of the main channel may not have completely closed during winter. In contrast, sites further from the main channel have a more dramatic response to meltwater input, as the area will become rapidly connected (Type B). This will occur at different times, associated with water accumulation and specific water passage through the till. At first, the channels cannot accommodate the extra discharge, and so there is a rapid increase in till water pressure, and possibly a speed-up event. Subsequently, the system becomes adapted to the high melt and water pressures can remain high.\u003c/p\u003e\n\u003cp\u003eThere have been numerous theoretical attempts to establish the characteristics that determine whether a channelized or distributed system will form associated with soft beds\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. These investigate the relative properties of ice and sediment and ice surface slope. We suggest that our results indicate the importance of sediment grain size. The subglacial till at Briksdalsbreen is coarse (very coarse sand) and we suggest that at the beginning of the melt season, as the distributed system grows, a low pressure channel is formed from sediment erosion. This rapidly draws water from the surrounding till, and this channel remains relatively stable\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. This results in spatial variation in subglacial till water pressures across the bed, including areas of over pressurization. In contrast, at the Icelandic sites, the presence of the finer grained till (ranging from coarse silt to fine sand) results in the development of the multichannel form and a spatially similar low summer effective pressure pattern.\u003c/p\u003e\n\u003cp\u003eWe propose that the members of this subglacial hydrology continuum have a set of distinct velocity patterns that may be used to identify the subglacial hydrology in regions where air temperatures periodically rise above zero during winter (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The difference between the braided system and the better-known channelized system is as follows: Since water is stored in the braided system itself, this is released in a series of winter events which are either absent from the channelised system, or fewer in number. By spring, much of the stored water in the braided system has already been released, and so a period of spring melting is required to generate enough water for a speed-up event. In contrast, in the channelized system the spring inputs immediately overwhelms the capacity of the system, resulting in a fast and distinct speed-up event. In summer, in the braided system, the constantly changing anastomosing allows the velocity to remain relatively stable, whilst in the channelized system, the development of the weakly connected drainage reduces the velocity. However, by the end of summer the systems are relatively so autumn velocity increases are observed in both systems.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u0026ndash; Criterion to identify subglacial hydrology based on seasonal velocity changes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBraided\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDrained Braided\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChannelized\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWinter\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWinter events\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo/few winter events\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo/few winter events\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSpring\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lsquo;Slow\u0026rsquo; speed-up event\u0026thinsp;~\u0026thinsp;15 days after the beginning of spring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lsquo;Fast\u0026rsquo; speed-up event at the beginning of spring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lsquo;Fast\u0026rsquo; speed-up event at the beginning of spring\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSummer\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSlow decrease over the summer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSlow decrease over the summer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFast decrease over the summer\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAutumn\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh velocities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh velocities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh velocities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eSince Brei\u0026eth;amerkurj\u0026ouml;kull has a drained braided subglacial hydrology it demonstrates a mix of the criterion. As it has low storage, there is limited response to winter events and a dramatic early spring event similar to the channelized system. However, during summer it behaves in a similar way to the braided system and has a relatively constant summer velocity as a result.\u003c/p\u003e\n\u003cp\u003eStick-slip motion was observed at Sk\u0026aacute;lafellsj\u0026ouml;kull throughout the year driven by meltwater and comprised four phases. During the melt season this occurred on a diurnal scale, with meltwater entering the system in the morning, which continually increases until a threshold is crossed, at which point the subglacial hydrology is overwhelmed, and there is a period of glacier sliding (Phase 1). Subsequently, the glacier reconnects with the bed and there is deformation (Phase 2). As temperatures and meltwater decline in the afternoon/evening, velocities are at their slowest and deformation is low (Phase 3), and then as temperatures begin to warm the next morning, the glacier begins to speed up and deformation increases (Phase 4). In winter, there is a similar multi-day pattern associated with meltwater from the winter events. The sliding phase is accompanied by a decline in water pressure and antithetic (backwards) change in tilt associated with unloading\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e (Phase A). The reconnection phase has very high synthetic tilt (Phase B), and then there is a period of stick with no tilt movement as water pressures fall below that able to produce deformation (Phase C). Finally, there is a final phase of increasing water pressures and synthetic tilt movement (Phase D).\u003c/p\u003e\n\u003cp\u003eWe can extend this interpretation to the other glaciers in the study (see Methods) and based on these observations, it was possible to calculate the amount of time that these processes occur in both summer and winter, and for the whole year. We can divide the time into three main states: i) sliding (Phase 1 \u0026amp; A); ii) deformation (Phases 2\u0026ndash;4 \u0026amp; B, D); and iii) no deformation (Phase C). In this way we have a quantification of subglacial processes (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u0026ndash; Calculation of different time periods for subglacial processes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth colspan=\"2\" rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003eSk\u0026aacute;lafellsj\u0026ouml;kull\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003eFjallsj\u0026ouml;kull\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003eBrei\u0026eth;amerkurj\u0026ouml;kull\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003eBriksdalsbreen\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMelt season %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWinter %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWhole year %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMelt season %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWinter %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWhole year %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMelt season %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWinter %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWhole year %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMelt season %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWinter %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWhole year %\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e1/A \u0026ndash;Sliding\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eassociated with the speed-up event\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e2/B- Deformation associated with reconnection\u003c/em\u003e as glacier slows down\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eLow deformation associated with velocity minimum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eStick\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e4/D- Deformation associated with reactivation\u003c/em\u003e as glacier begins to speed up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAnnual Sliding\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eDeformation\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNo deformation\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e#\u003cem\u003eThe value is different to that previously quoted\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eas those only included one year, whilst the figure above is a mean of two years.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe pattern at Fjallsj\u0026ouml;kull was very similar to Sk\u0026aacute;lafellsj\u0026ouml;kull. However, at Brei\u0026eth;amerkurj\u0026ouml;kull, during summer there is double diurnal velocity peak and in winter 81% of the winter events were accompanied by more than one sliding event, many of which were not related to weather conditions, whilst 55% of cycles did not have a sliding phase at the beginning, and there was a lag before sliding occurred. At Briksdalsbreen the pattern in the melt season was similar to Sk\u0026aacute;lafellsj\u0026ouml;kull, but in winter there were two speed-up events during each winter event. The first is associated with the build-up of porewater pressure due to the restriction of water moving through the till. The second is due to melt water production associated with rising temperatures. In this way Briksdalsbreen has two sliding episodes in each winter event, but the number of events per year is very low, so there is only 4% sliding during the winter.\u003c/p\u003e\n\u003cp\u003eOverall, our study glaciers have a relatively similar pattern but with some small differences. For those glaciers associated with a braided system (Sk\u0026aacute;lafellsj\u0026ouml;kull and Fjallsj\u0026ouml;kull) sliding represents 13\u0026ndash;14% of the year, deformation 69% of the year, with no deformation occurring 17\u0026ndash;18% of the year; whilst at those associated with a channelized system (Briksdalsbreen) there are similar levels of sliding (12%) slightly lower deformation (65%) and slightly higher periods of no deformation (23%). However, this overall pattern includes seasonal differences: in the channelised system sliding was high in summer, but very low in winter.\u003c/p\u003e\n\u003cp\u003eIn the intermediate system (Brei\u0026eth;amerkurj\u0026ouml;kull) there is slightly higher annual sliding (19%), similar deformation (70%) and shorter periods of no deformation (11%). Much of this variation is due to the higher levels of sliding during the melt season related to the double velocity peaks. In winter, although there were fewer and slower speed-up events related to the winter events there were numerous non-weather-related events which we have suggested were due to calving.\u003c/p\u003e\n\u003cp\u003eWe have proposed that the different subglacial hydrology\u0026rsquo;s are associated with different subglacial processes. This may be useful in reconstructing the rate and nature of processes associated with Quaternary tills. Sliding may be associated with lodgement till\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, whilst the deformation recorded at our sites will a result in deformation till\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Glacio-fluvial elements within tills may also be important indicators. Classically eskers are associated with channelized drainage\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e, whilst the sedimentary remains of \u0026lsquo;canals\u0026rsquo;, \u0026lsquo;subglacial meltwater corridors\u0026rsquo; and murtoos\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e may reflect the braided system. Stratified lenses within till are common and have been given numerous interpretations, either reflecting preglacial outwash that have been incorporated into the till, usually by attenuation and boudinage\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e or penecontemporaneous sedimentation with the till either in a braided system\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e or at the ice sediment interface\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. These are very often subsequently deformed as they are deposited associated with a deforming bed. Our study highlights that we would expect to find sedimentary evidence for a braided system in subglacial tills, and these would very likely be deformed given the high duration of deformation associated with a braided system (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUnderstanding subglacial behaviour is a key element in understand glacier response to climate change and global sea level prediction. We have proposed a unique methodology to identify subglacial hydrology from Sentinel-1 SAR imagery, supported by Glacsweb \u003cem\u003ein situ\u003c/em\u003e probe and daily GPS data. This hypothesis has the potential to enable the subglacial regime of numerous glaciers to be identified, and in particular test the relative occurrence of different subglacial hydrological systems associated with soft-bedded glaciers worldwide. We have also discussed the different subglacial processes associated with these different subglacial hydrological systems. This model now needs to be tested at other locations, and the detailed glaciological effects of these different hydrological systems examined.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eEnvironmental Sensor Network and the Glacsweb in-situ wireless probes\u003c/h2\u003e \u003cp\u003eAn environmental sensor network system was designed to collect the in-situ probe data, comprising sensor nodes and base stations, which are linked together by radio networks. Data was recorded from the probes at Briksdalsbreen (2004\u0026ndash;2006) every four hours and at Sk\u0026aacute;lafellsj\u0026ouml;kull initially every hour (2008\u0026ndash;2010), and then every 15 minutes during 2012. Their data was transmitted from base stations via GPRS to a cloud server and hence to a sensor network server in the UK. Node data, along with differential GPS (dGPS) recordings and meteorological data, were sent once a day to a mains powered computer (5 km at Briksdalsbreen, 16 km Sk\u0026aacute;lafellsj\u0026ouml;kull), where it was forwarded to a web server in the UK\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe specific site location on the glacier was determined by the optimal depth at which the system can transmit data through the till and ice (50\u0026ndash;80 m). These probes were deployed in the summers of 2004, 2005, 2008 and 2012, in a series of boreholes, which were drilled with a K\u0026auml;rcher HDS1000DE jet wash system. Once the boreholes were made, the glacier and till were examined using a custom-made CCD colour video camera with infrared LED illumination. If till was present it was hydraulically excavated\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e by maintaining the jet at the bottom of the borehole for an extended period of time. The probes were then lowered into this space, enabling the till to subsequently close in around them. The depth of the probes (in the till) was estimated from video footage of the ice/till interface to be ~\u0026thinsp;0.1\u0026ndash;0.3 m at Briksdalsbreen and ~\u0026thinsp;0.1\u0026thinsp;\u0026minus;\u0026thinsp;0.2 m at Sk\u0026aacute;lafellsj\u0026ouml;kull beneath the glacier base.\u003c/p\u003e \u003cp\u003eThese water pressure data were calibrated against the measured water depths in the borehole immediately after probe deployment. The glacier thickness (\u003cem\u003eH\u003c/em\u003e) was determined from measuring the depth of the boreholes and comparing with the GPS data of the glacier surface. Effective pressure N is calculated as follows:\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;P\u003csub\u003ei\u003c/sub\u003e -P\u003csub\u003ew\u003c/sub\u003e\u003c/p\u003e \u003cp\u003ewhere P\u003csub\u003ei\u003c/sub\u003e = pressure of ice, and Pw\u0026thinsp;=\u0026thinsp;water pressure.\u003c/p\u003e \u003cp\u003ePi\u0026thinsp;=\u0026thinsp;\u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u003cem\u003egH\u003c/em\u003e\u003c/p\u003e \u003cp\u003eWhere \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e =\u003c/sub\u003e density of ice (910 kg m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e), \u003cem\u003eg\u003c/em\u003e\u0026thinsp;=\u0026thinsp;gravity (9.8 m s\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) and \u003cem\u003eH\u003c/em\u003e\u0026thinsp;=\u0026thinsp;ice thickness.\u003c/p\u003e \u003cp\u003eIn addition, custom-made, low-power geophones were installed within boreholes to avoid surface seismic noise. The geophone nodes continually sampled the output of three orthogonal geophones but only data from seismic events were stored, held temporarily on a micro-SD card until they were retrieved by the base station. We used a 25 dB amplifier to provide sufficient signal with a bandpass pre-filter of 0.5\u0026ndash;234 Hz, and a sampling rate of 512 Hz\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eInternet of Things Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS)\u003c/h2\u003e \u003cp\u003eWe designed and built a unique low-cost, internet connected (with real-time solutions) GNSS with which to measure movement in remote locations. This was installed at Fjallsj\u0026ouml;kull and Brei\u0026eth;amerkurj\u0026ouml;kull (2017\u0026ndash;2020). The system comprises a base station, one or more rovers and a server receiving the data. It was based on L1/L2 dGPS from Swift Navigation (Piksi Multi), which use 3W when operating, providing a typical accuracy of 2 cm after 40s fix time and receive corrections from GPS, GLONASS and Galileo satellites. They are only powered on when taking readings to save battery lifetime.\u003c/p\u003e \u003cp\u003eThe system was controlled by an ARM M4 microcontroller (96 kB RAM, 384 kB flash), which has a sleep current of 6 \u0026micro;A and ran micropython. Synchronised base station units were placed in the foreland, which transmitted the dGPS corrections to the rovers according to the schedule. An Iridium short messaging unit (Rockblock) was used by the rovers to send 8 readings once per day (330 bytes) directly to our database, allowing daily updates of data interpretation.\u003c/p\u003e \u003cp\u003eThe annual data were collected by Version 1 of the system which operated 2017\u0026ndash;2020. The data shown is from Fjallsj\u0026ouml;kull, located where the ice was ~\u0026thinsp;77 m deep, and Brei\u0026eth;amerkurj\u0026ouml;kull where the ice was 84 m thick. The summer diurnal data were collected from Version 2 of the system installed in 2024, which was installed in a similar location.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eVelocity records\u003c/h2\u003e \u003cp\u003eIce surface velocity was measured at Sk\u0026aacute;lafellsj\u0026ouml;kull from 2008\u0026ndash;2012 with a TOPCON Legacy-H L1/L2 GPS (1 km baseline), and from 2012\u0026ndash;2013 with an additional array of 4 dual frequency Leica 1200 GPS systems which obtained data continuously during the summer and 2 h a day during the winter at a 15 s sampling rate (300 m baseline). The GPS data were then processed using data from the International GPS Service (IGS) reference stations using TRACK (v. 1.24), the kinematic software package developed by Massachusetts Institute of Technology (MIT) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://geoweb.mit.edu/~tah/track_example/\u003c/span\u003e\u003cspan address=\"http://geoweb.mit.edu/~tah/track_example/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). We derived an average surface horizontal velocity by taking the mean of 4 GPS stations to remove local variations. To account for surface melting, we removed the daily melt from the vertical measurements. The mean error estimates were as follows (sigma per day): North +/\u0026minus; 0.0045 m, east +/\u0026minus; 0.0032 m, height +/\u0026minus; 0.0092 m. We have previously demonstrated\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e that velocity has a distinct pattern related to air temperature and utilised a transfer function to reconstruct a velocity record for 2009/10 using the velocity data from 2012/13.\u003c/p\u003e \u003cp\u003eAt Fjallsj\u0026ouml;kull and Brei\u0026eth;amerkurj\u0026ouml;kull, the surface velocity was measured with the web connected RTK GNSS system discussed above. The error estimates were +/- 2 cm.\u003c/p\u003e \u003cp\u003eSentinel-1 SAR imagery was also used to calculate glacier-wide velocities at 12-day repeat intervals. Data were generated using the offset tracking algorithm within the European Space Agency (ESA) Sentinel Application Platform (SNAP). Although offset tracking is less precise than SAR interferometry, given the high temporal correlation of glacier surfaces, it is much more robust, and as such the method is widely used in glacier motion assessment\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. Here, each pair of SAR images were first calibrated and then co-registered using the aerial LiDAR DEM of Iceland, provided at 10 m resolution by the National Land Survey of Iceland. Velocities were then calculated using cross correlation, with specific parameters, including the moving window size and search distance, varying between each glacier (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProcessing parameters used in SNAP to produce velocity rasters of each glacier.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlacier\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrid Azimuth Spacing (pixels)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrid Range Spacing (pixels)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRegistration Window Width/Height\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMax. Velocity (m d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSk\u0026aacute;lafellsj\u0026ouml;kull\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64 x 64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrei\u0026eth;amerkurj\u0026ouml;kull\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e256 x 256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFjallsj\u0026ouml;kull\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e128 x 128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBriksdalsbreen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64 x 64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAny displacements with a cross-correlation threshold of \u0026lt;\u0026thinsp;0.01 were then removed, with the remaining displacements averaged over a mean pixel grid and converted to ground range coordinates, resulting in velocity rasters at 10 m resolution. The stochastic error in our velocity measurements was assessed by measuring displacements over terrain that we regarded as stable\u003csup\u003e71,72\u003c/sup\u003e.The average RMSE for the Sentinel-1 imagery over the entire period was +/\u0026minus;0.15 m per day. This was calculated from June 2017 to Oct 2020. Mean velocities and errors were then calculated along the centre line of the glaciers.\u003c/p\u003e \u003cp\u003eWe calculated the change in 12-day velocity over the summer by comparing the maximum velocity during the spring with the lowest velocity just prior to the autumn velocity rise, which we express as a percentage. We do this for each year, taking a mean for each glacier.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAir temperature records, defining the seasons and determining the relationship between winter events and velocity change\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAir temperature data were primarily obtained from the base stations described above but during periods of mechanical failure, a transfer function was applied to data from neighbouring meteorological stations. For Sk\u0026aacute;lafellsj\u0026ouml;kull we used Hofn (~\u0026thinsp;30 km away), for Fjallsj\u0026ouml;kull and Brei\u0026eth;amerkurj\u0026ouml;kull we used Kvisker (~\u0026thinsp;6 and ~\u0026thinsp;16 km away respectively) and for Briksdalsbreen we used Stryn (~\u0026thinsp;30 km away).\u003c/p\u003e \u003cp\u003eWe define the seasons based on air temperatures, and since the sites have different mean annual temperatures (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) we utilised slightly different seasonal thresholds. Winter is a time where there is little melting as temperatures are low. We have used the mean annual air temperature as this threshold (Sk\u0026aacute;lafellsj\u0026ouml;kull 0\u003csup\u003eo\u003c/sup\u003eC, Fjallsj\u0026ouml;kull and Brei\u0026eth;amerkurj\u0026ouml;kull 5\u003csup\u003eo\u003c/sup\u003eC, and Briksdalsbreen 6\u003csup\u003eo\u003c/sup\u003eC). Spring begins once the daily temperatures are continuously above the winter threshold, summer is reflected by much higher temperatures (~\u0026thinsp;5\u003csup\u003eO\u003c/sup\u003eC higher than the winter threshold), autumn temperatures are lower often falling below zero at night.\u003c/p\u003e \u003cp\u003eWe quantified the glacier response to the winter events in two ways. For the daily velocity data from GPS, we counted the percentage of events where the speed-up event occurred at the same time as a temperature rise above the threshold. For the 12-day velocity data from Sentinel-1, we calculated the number of days within each period that air temperatures were above the threshold (N). We assumed that if the value of N was zero, it would reflect a base (low) velocity, it if were above zero it would reflect a speed-up event (high velocity). We then calculated the percentage of \u0026lsquo;correct\u0026rsquo; attributions over the winter. We set the threshold between low and high velocity at 95% of the winter velocity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDetermining the different phases of stick-slip motion\u003c/h2\u003e \u003cp\u003eThe initial determination of the different phases of stick-slip motion were calculated from the tilt, geophone, velocity and air temperature data from Sk\u0026aacute;lafellsj\u0026ouml;kull. There are four phases (diurnal in melt season indicated by a number, multi-day in winter by a letter): sliding (Phase 1/A), reconnection (Phase 2/B), low or no deformation (Phase 3/C), reactivation (Phase 4/D). We were able to extend this analysis to the other glaciers in the study. At Fjallsj\u0026ouml;kull and Brei\u0026eth;amerkurj\u0026ouml;kull, although we do not have tilt or geophone data, the data from Sk\u0026aacute;lafellsj\u0026ouml;kull clearly illustrate a relationship between tilt and velocity, so that velocity can be used as proxy for tilt in the analyses. Although the velocities from Sk\u0026aacute;lafellsj\u0026ouml;kull were very similar during Stages C and D, they could be distinguished using air temperature: Stage C occurred when temperatures were low (below zero), whilst Stage D was associated with rising temperatures (just before the threshold for the winter event to occur). This enabled us to isolate the two stages at Fjallsj\u0026ouml;kull and Brei\u0026eth;amerkurj\u0026ouml;kull: Stage C was associated with low velocity and low air temperatures (less than 5\u0026deg;C), and Stage D with rising air temperatures (and occasionally higher velocity).\u003c/p\u003e \u003cp\u003eAt Briksdalsbreen, where tilt data was available but not velocity, it was possible to use these alongside air temperatures to identify the different phases. During the melt season, there was a distinct daily pattern. As air temperatures (and presumably velocities) rise in the morning they are accompanied at midday by low tilt change, which we suggest reflects sliding (Phase 1). During the afternoon, there was an increase in tilt change, which we suggest reflects reconnection with the bed (Phase 2) and deformation throughout the afternoon and evening. Tilt motion/deformation is then lowest at midnight (Phase 3), before increasing slightly throughout the morning as the glaciers speeds up in response to increasing melt (Phase 4). During winter, there was also a pattern of stick-slip motion but with a more complex, double configuration. When temperatures drop below zero, water pressures rise, until a water pressure threshold is crossed (after ~\u0026thinsp;four days), and we assume there is a speed-up event that generates the antithetic behaviour and sliding (Phase A) (Fig.\u0026nbsp;4a, DOY 23). After this the glacier slows down and reconnects with the bed, resulting in deformation (indicated by the large synthetic tilt movement) (Phase B) (Fig.\u0026nbsp;4a, DOY 24). If the water pressure is sufficiently high then there will not be a stick phase, but rather continuous low synthetic deformation. This is often indistinguishable from the reconnection Stage D (Fig.\u0026nbsp;4a, DOY 25\u0026ndash;34) so we have grouped the two together. Then as air temperatures again rise above zero we see a pattern similar to Sk\u0026aacute;lafellsj\u0026ouml;kull. Firstly, meltwater enters the system, resulting in sliding and antithetic deformation (Phase A) (Fig.\u0026nbsp;4a, DOY 35), then a dramatic decline in water pressure associated with synthetic tilt (Phase B) (Fig.\u0026nbsp;4a, DOY 36), followed by a period of stick (Phase C) (seen in event 1) or low deformation (Phase D) (Fig.\u0026nbsp;4a, DOY 37\u0026ndash;42) (seen in the rest of the events) depending on porewater pressures.\u003c/p\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eData Availability\u003c/h2\u003e \u003cp\u003eData is available at Glacsweb.org (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.glacsweb.info/datasets/\u003c/span\u003e\u003cspan address=\"https://data.glacsweb.info/datasets/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and a DOI will be provided on publication.\u003c/p\u003e \u003c/div\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the Glacsweb 2003-2024 teams for help with probe development and data collection. They would also like to thank Matthew Roberts of the Icelandic Meteorological office for his advice and support. We would also like to thank Dr Phillip Basford and Josh Curry and for help with design of the Smart tracker and database. The authors also thank Eyj\u0026oacute;lfur Magn\u0026uacute;sson for sharing his bedrock topography data for Fjallsj\u0026ouml;kull. This research was funded by EPSRC (EP/C511050/1), Leverhulme (F/00180/AK, RPG-2021-316) and the National Geographic (GEFNE45-12, NGS-368R-18) and the GPR and Leica 1200 GPS units were loaned from the NERC Geophysical Equipment Facility.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.K.H. and K.M. designed the study. J.K.H. carried out the probe, discharge and GNSS data analysis. K.M. and G.B. designed the sensor network system, Glacsweb probes and web connected GNSS system as well as the software. N.R.B., B.A.R., A.B derived the remotely sensed surface velocity. J.K.H. wrote the manuscript with input from all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZemp, M., Huss, M., Thibert, E., Eckert, N., McNabb, R., Huber, J., Barandun, M., Machguth, H., Nussbaumer, S.U., G\u0026auml;rtner-Roer, I. \u0026amp; Thomson, L. Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016. \u003cem\u003eNature\u003c/em\u003e 568(7752), 382 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrederikse, T., Landerer, F., Caron, L., Adhikari, S., Parkes, D., Humphrey, V.W., Dangendorf, S., Hogarth, P., Zanna, L., Cheng, L. \u0026amp; Wu, Y.H. The causes of sea-level e since 1900. 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The Sentinel-1 mission: New opportunities for ice sheet observations. \u003cem\u003eRemote Sensing\u003c/em\u003e, 7(7), 9371\u0026ndash;9389 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRobson, B.A., Nuth, C., Nielsen, P.R., Girod, L., Hendrickx, M. \u0026amp; Dahl, S.O. Spatial variability in patterns of glacier change across the Manaslu Range, Central Himalaya. Frontiers in Earth Science 6, 1\u0026ndash;12 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaurley, N.R., Robson, B., \u0026amp; Hart, J.K. Long-term impact of the proglacial lake J\u0026ouml;kuls\u0026aacute;rl\u0026oacute;n on the flow velocity and stability of Brei\u0026eth;amerkurj\u0026ouml;kull glacier, Iceland. \u003cem\u003eEarth Surface Processes and Landforms\u003c/em\u003e 45 (11), 2647\u0026ndash;2663 (2020).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4539760/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4539760/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe use a series of unique techniques (wireless \u003cem\u003ein situ\u003c/em\u003e subglacial probes; web connected GNSS) along with remotely sensed data to record a continuum of subglacial hydrology from channelized to braided behaviour associated with four soft bedded temperate glaciers. We argue this continuum may be affected by till grain size and subaqueous processes. In addition, we are able to quantify sedimentary processes associated with these different hydrologies. Although we have used a multi-data stream here, we suggest it is possible to solely use glacier velocity data, derived from Sentinel-1 imagery, to distinguish the different hydrological types. This is important because the water at the base of the glacier (in both water bodies and the till) is a key driver of glacier behaviour and the rate of sea level rise, but direct measurements of the basal environment are rare, hence the importance of our remote sensing data.\u003c/p\u003e","manuscriptTitle":"Seasonal velocity patterns and deforming bed processes associated with different subglacial drainage systems.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-03 15:18:13","doi":"10.21203/rs.3.rs-4539760/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-earth-and-environment","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsenv","sideBox":"Learn more about [Communications Earth and Environment](https://www.nature.com/commsenv/)","snPcode":"","submissionUrl":"","title":"Communications Earth \u0026 Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"36e6e6c5-eaec-4de7-8c82-6aeb0b10deba","owner":[],"postedDate":"July 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33110927,"name":"Earth and environmental sciences/Hydrology"},{"id":33110928,"name":"Earth and environmental sciences/Climate sciences"}],"tags":[],"updatedAt":"2025-03-22T07:09:36+00:00","versionOfRecord":{"articleIdentity":"rs-4539760","link":"https://doi.org/10.1038/s43247-025-02198-0","journal":{"identity":"communications-earth-and-environment","isVorOnly":false,"title":"Communications Earth \u0026 Environment"},"publishedOn":"2025-03-21 04:00:00","publishedOnDateReadable":"March 21st, 2025"},"versionCreatedAt":"2024-07-03 15:18:13","video":"","vorDoi":"10.1038/s43247-025-02198-0","vorDoiUrl":"https://doi.org/10.1038/s43247-025-02198-0","workflowStages":[]},"version":"v1","identity":"rs-4539760","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4539760","identity":"rs-4539760","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}