Abstract:Surface melting impacts ice sheet sliding by supplying water to the bed, but subglacial processes driving ice accelerations are complex. We examine linkages between surface runoff, transient subglacial water storage, and short‐term ice motion from 168 consecutive hourly measurements of meltwater discharge (moulin input) and GPS ‐derived ice surface motion for Rio Behar, a ∼60 km2 moulin‐terminating supraglacial river catchment on the southwest Greenland Ice Sheet. Short‐term accelerations in ice speed correlate… Show more
“…Solving Eqn (15) initially assuming κ = 600 km 2 d −1 and ɛ = 0 gives results shown in Figure 3. The predicted proglacial output is qualitatively similar to the observed proglacial discharge, with a predicted decline of the perturbation amplitude from ~70% at the inlet to ~7% proglacially and time lag of the discharge of ~12 h. Comparing this to the observations by Smith and others (2021) of the perturbation amplitude declining from ~70 to 9%, the model is reasonable, especially considering that the proglacial discharge is affected by numerous other moulins other than the one fed by Rio Behar and thus should not be expected to be quantitatively matched by the model, even if the model framework were correct. Fig.…”
Section: Resultssupporting
confidence: 81%
“…To test the combined hydrologic and sliding model against observations, we compare its predictions with field observations from Smith and others (2021) in southwest Greenland. This study collected hourly in situ discharge measurements in a large supraglacial river (‘Rio Behar’), together with local ice surface velocities from GPS, just upstream of a major moulin (see Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Observations have demonstrated that transient water input can drive significant increases in glacier surface velocity (Iken and others, 1983; Iken and Bindschadler, 1986; Zwally and others, 2002; Bartholomew and others, 2010; Andrews and others, 2014; Cowton and others, 2016; Smith and others, 2021), but also that sustained water input can lead to slower velocities, particularly later in the melt season (Tedstone and others, 2015). The way in which water inputs affect subglacial water pressure, and hence sliding velocities, is thought to be dependent on the hydraulic conductivity at glacier bed.…”
Changes in water pressure at the beds of glaciers greatly modify their sliding rate, affecting rates of ice mass loss and sea level change. However, there is still no agreement about the physics of subglacial sliding or how water affects it. Here, we present a new simplified physical model for the effect of transient subglacial hydrology on basal ice velocity. This model assumes that a fraction of the glacier bed is connected by an active hydrologic system that, when averaged over an appropriate scale, is governed by two parameters with limited spatial variability. The sliding model is reminiscent of Budd's empirical sliding law but with fundamental differences including a dependence on the fractional area of the active hydrologic system. With periodic surface meltwater forcing, the model displays classic diffusion-wave behavior, with a downstream time lag and decay of subglacial water pressure perturbations. Testing the model against Greenland observations suggests that, despite its simplicity, it captures key features of observed proglacial discharges and ice velocities with reasonable physical parameter values. Given these encouraging findings, including this sliding model in predictive ice-sheet models may improve their ability to predict time-evolving velocities and associated sea level change and reduce the related uncertainties.
“…Solving Eqn (15) initially assuming κ = 600 km 2 d −1 and ɛ = 0 gives results shown in Figure 3. The predicted proglacial output is qualitatively similar to the observed proglacial discharge, with a predicted decline of the perturbation amplitude from ~70% at the inlet to ~7% proglacially and time lag of the discharge of ~12 h. Comparing this to the observations by Smith and others (2021) of the perturbation amplitude declining from ~70 to 9%, the model is reasonable, especially considering that the proglacial discharge is affected by numerous other moulins other than the one fed by Rio Behar and thus should not be expected to be quantitatively matched by the model, even if the model framework were correct. Fig.…”
Section: Resultssupporting
confidence: 81%
“…To test the combined hydrologic and sliding model against observations, we compare its predictions with field observations from Smith and others (2021) in southwest Greenland. This study collected hourly in situ discharge measurements in a large supraglacial river (‘Rio Behar’), together with local ice surface velocities from GPS, just upstream of a major moulin (see Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Observations have demonstrated that transient water input can drive significant increases in glacier surface velocity (Iken and others, 1983; Iken and Bindschadler, 1986; Zwally and others, 2002; Bartholomew and others, 2010; Andrews and others, 2014; Cowton and others, 2016; Smith and others, 2021), but also that sustained water input can lead to slower velocities, particularly later in the melt season (Tedstone and others, 2015). The way in which water inputs affect subglacial water pressure, and hence sliding velocities, is thought to be dependent on the hydraulic conductivity at glacier bed.…”
Changes in water pressure at the beds of glaciers greatly modify their sliding rate, affecting rates of ice mass loss and sea level change. However, there is still no agreement about the physics of subglacial sliding or how water affects it. Here, we present a new simplified physical model for the effect of transient subglacial hydrology on basal ice velocity. This model assumes that a fraction of the glacier bed is connected by an active hydrologic system that, when averaged over an appropriate scale, is governed by two parameters with limited spatial variability. The sliding model is reminiscent of Budd's empirical sliding law but with fundamental differences including a dependence on the fractional area of the active hydrologic system. With periodic surface meltwater forcing, the model displays classic diffusion-wave behavior, with a downstream time lag and decay of subglacial water pressure perturbations. Testing the model against Greenland observations suggests that, despite its simplicity, it captures key features of observed proglacial discharges and ice velocities with reasonable physical parameter values. Given these encouraging findings, including this sliding model in predictive ice-sheet models may improve their ability to predict time-evolving velocities and associated sea level change and reduce the related uncertainties.
“…Understanding the spatial distribution of these features can facilitate a more process-based understanding of satellite-derived albedo measurements (Moustafa et al, 2015). In turn, this improved understanding can aid climate model calculations of surface mass balance (Enderlin et al, 2014;Ryan et al, 2018) and dynamic losses from hydrofracturing and runoff induced ice acceleration (McGrath et al, 2012;Smith et al, 2021). Additionally, knowing the extent of hydrologic features on the surface of Antarctica can help improve predictions of ice shelf instability (McGrath et al, 2012).…”
The presence of shadows in remotely sensed images can reduce the accuracy of land surface classifications. Commonly used methods for removing shadows often use multi-spectral image analysis techniques that perform poorly for dark objects, complex geometric models, or shaded relief methods that do not account for shadows cast on adjacent terrain. Here we present a new method of removing topographic shadows using readily available GIS software. The method corrects for cast shadows, reduces the amount of over-correction, and can be performed on imagery of any spectral resolution. We demonstrate this method using imagery collected with an uncrewed aerial vehicle (UAV) over a supraglacial stream catchment in southwest Greenland. The structure-from-motion digital elevation model showed highly variable topography resulting in substantial shadowing and variable reflectance values for similar surface types. The distribution of bare ice, sediment, and water within the catchment was determined using a supervised classification scheme applied to the corrected and original UAV images. The correction resulted in an insignificant change in overall classification accuracy, however, visual inspection showed that the corrected classification more closely followed the expected distribution of classes indicating that shadow correction can aid in identification of glaciological features hidden within shadowed regions. Shadow correction also caused a substantial decrease in the areal coverage of dark sediment. Sediment cover was highly dependent on the degree of shadow correction (k coefficient), yet, for a correction coefficient optimized to maximize shadow brightness without over-exposing illuminated surfaces, terrain correction resulted in a 49% decrease in the area covered by sediment and a 29% increase in the area covered by water. Shadow correction therefore reduces the overestimation of the dark surface coverage due to shadowing and is a useful tool for investigating supraglacial processes and land cover change over a wide variety of complex terrain.
“…controls the timing and magnitude of diurnally varying moulin input, which in turn influences subglacial hydrology and ice flow dynamics (Andrews et al, 2014;Banwell et al, 2013;Clason et al, 2015;Davison et al, 2019;Decaux et al, 2019;de Fleurian et al, 2016;Koziol & Arnold, 2018;Schoof, 2010;Smith et al, 2021). Accurate simulation of moulin input hydrographs therefore requires high-resolution, multi-temporal mapping of supraglacial stream/river networks, so as to partition catchment drainage areas into channelized versus non-channelized flow (Yang et al, 2018).…”
Supraglacial stream/river catchments drain large volumes of surface meltwater off the southwestern Greenland Ice Sheet (GrIS) surface. Previous studies note a strong seasonal evolution of their drainage density (Dd), a classic measure of drainage efficiency defined as open channel length per unit catchment area, but a direct correlation between Dd and surface meltwater runoff (R) has not been established. We use 27 high-resolution (~0.5 m) satellite images to map seasonally evolving Dd for four GrIS supraglacial catchments, with elevations ranging from 1100 m to 1700 m. We find a positive linear correlation (r 2 = 0.70, p<0.01) between Dd and simulations of runoff production from two climate models (MAR v3.11 and MERRA-2). Applying this R-Dd empirical relationship to climate model output enables parameterization of spatial and temporal changes in supraglacial drainage efficiency continuously throughout the melt season, although temporal and spatial skewness of Dd observations likely affects the application of this R-Dd relationship on crevasse fields and snow/firn surfaces. Incorporating this information into a simple surface routing model finds that high runoff leads to earlier, larger diurnal peaks of runoff transport on the ice surface, owing to increased Dd. This effect progressively declines from low (~1100 m) to high (~1700 m) elevation, causing a roughly order-of-magnitude reduction in diurnal runoff variability at the highest elevations relative to standard climate model output. Combining intermittent satellite Dd mapping with climate model output thus promises to improve characterization of supraglacial drainage efficiency to the benefit of supraglacial meltwater routing and subglacial hydrology models.
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