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Abstract. Subglacial meltwater channels (N-channels) are attributed to erosion by meltwater in subglacial conduits. They exert a major control on meltwater accumulation at the base of ice sheets, serving as drainage pathways and modifying ice flow rates. The study of exposed relict subglacial channels offers a unique opportunity to characterize the geomorphologic fingerprint of subglacial erosion as well as study the structure and characteristics of ice sheet drainage systems. In this study we present detailed field and remote sensing observations of exposed subglacial meltwater channels in excellent preservation state on Devon Island (Canadian Arctic Archipelago). We characterize channel cross section, longitudinal profiles, and network morphologies and establish the spatial extent and distinctive characteristics of subglacial drainage systems. We use field-based GPS measurements of subglacial channel longitudinal profiles, along with stereo imagery-derived digital surface models (DSMs), and novel kinematic portable lidar data to establish a detailed characterization of subglacial channels in our field study area, including their distinction from rivers and other meltwater drainage systems. Subglacial channels typically cluster in groups of ∼10 channels and are oriented perpendicular to active or former ice margins. Although their overall direction generally follows topographic gradients, channels can be oblique to topographic gradients and have undulating longitudinal profiles. We also observe that the width of firstorder tributaries is 1 to 2 orders of magnitude larger than in Devon Island river systems and approximately constant. Furthermore, our findings are consistent with theoretical expectations drawn from analyses of flow driven by gradients in effective water pressure related to variations in ice thickness. Our field and remote sensing observations represent the first high-resolution study of the subglacial geomorphology of the high Arctic, and provide quantitative and qualitative descriptions of subglacial channels that revisit well-established field identification guidelines. Distinguishing subglacial channels in topographic data is critical for understanding the emergence, geometry, and extent of channelized meltwater systems and their role in ice sheet drainage. The final aim of this study is to facilitate the identification of subglacial channel networks throughout the globe by using remote sensing techniques, which will improve the detection of these systems and help to build understanding of the underlying mechanics of subglacial channelized drainage.

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The morphology of channel networks related to long‐term erosion reflects the mechanisms involved in their formation. This study aims to identify quantitative metrics, drawn from topographic data and satellite imagery, that are diagnostic of the distinctive styles of erosion by rivers, glaciers, subglacial meltwater, and groundwater sapping. From digital elevation models, we identify three geometric metrics: the minimum channel width, channel aspect ratio (longest length to channel width at the outlet), and tributary junction angle. We also characterize channel network complexity in terms of its stream order and fractal dimension. To validate our approach, we perform a principal component analysis (PCA) on measurements of these five metrics on 70 channel networks. We build understanding of these results, in turn using scaling analyses of appropriate physical models. We show that rivers, glaciers, and groundwater sapping erode the landscape in rigorously distinguishable ways. Whereas rivers are characterized by nearly constant minimum width, variable aspect ratio, and high stream orders, glaciers have highly variable minimum widths and aspect ratios and much smaller stream orders. Erosion by subglacial meltwater remains poorly understood, and we argue that we require an additional metric to fully characterize these systems. Our methodology can more generally be applied to identify the contributions of different processes involved in carving a channel network. In particular, we are able to identify transitions from fluvial to glaciated landscapes or vice versa.