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As the global climate warms, increased surface meltwater production on ice shelves may trigger ice-shelf collapse and enhance global sea-level rise. The formation of surface rivers could help prevent ice-shelf collapse if they can efficiently evacuate meltwater. Here, we present observations of the evolution of a surface river into an ice-shelf estuary atop the Petermann Ice Shelf in northwest Greenland, and identify a second estuary at the nearby Ryder Ice Shelf. This surface hydrology process can foster fracturing and enhance calving. At the Petermann estuary, sea ice was observed converging at the river mouth upstream, indicating a flow reversal. Seawater persists in the estuary, after the surrounding icescape is frozen. Along the base of Petermann estuary, linear fractures were initiated at the calving front and propagated upstream along the channel. Similar fractures along estuary channels shaped past large rectilinear calving events at the Petermann and Ryder Ice Shelves. Increased surface melting in a warming world will enhance fluvial incision, promoting estuary development, longitudinal fracturing orthogonal to ice-shelf fronts, and increase rectilinear calving. Estuaries could develop in Antarctica within the next half-century, resulting in increased calving and accelerating both ice loss and global sea-level rise.

Glacial environments offer the opportunity to study the incipient stages of chemical weathering due to the high availability of finely ground sediments, low water temperatures, and typically short rock-water interaction times. In this study we focused on the geochemical behavior of germanium (Ge) in west Greenland, both during subglacial weathering by investigating glacier-fed streams, as well as during a batch reactor experiment by allowing water-sediment interaction for up to 2 years in the laboratory. Sampled in late August 2014, glacial stream Ge and Si concentrations were low, ranging between 12–55 pmol/L and 7–33 µmol/L, respectively (Ge/Si = 0.9–2.2 µmol/mol, similar to parent rock). As reported previously, the dissolved stable Ge isotope ratio (δ74Ge) of the Watson River was 0.86 ± 0.24‰, the lowest among global rivers and streams measured to date. This value was only slightly heavier than the suspended load (0.48 ± 0.23‰), which is likely representative of the bulk parent rock composition. Despite limited Ge/Si and δ74GeGe fractionation, both Ge and Si appear depleted relative to Na during subglacial weathering, which we interpret as the relatively congruent uptake of both phases by amorphous silica (aSi). Continued sediment-water interaction over 470–785 days in the lab produced a large increase in dissolved Si concentrations (up to 130–230 µmol/L), a much smaller increase in dissolved Ge (up to ∼70 pmol/L), resulting in a Ge/Si decrease (to 0.4–0.5 µmol/mol) and a significant increase in δ74Ge (to 1.9–2.2‰). We argue that during the experiment, both Si and Ge are released by the dissolution of previously subglacially formed aSi, and Ge is then incorporated into secondary phases (likely adsorbed to Fe oxyhydroxides), with an associated Δ74Gesecondary−dissolved fractionation factor of −2.15 ± 0.46‰. In summary, we directly demonstrate Ge isotope fractionation during the dissolution-precipitation weathering reactions of natural sediments in the absence of biological Ge and Si uptake, and highlight the significant differences in Ge behavior during subglacial and non-glacial weathering.

Surface water resources are vital for biological, physical, and socioeconomic processes on the Earth’s surface. To advance monitoring capabilities of these resources, new remote sensing technologies including the forthcoming Surface Water and Ocean Topography (SWOT) satellite (expected launch 2022) and its experimental airborne prototype AirSWOT are being developed to repeatedly map water surface elevation (WSE) and slope (WSS) of the world’s rivers, lakes, and reservoirs. However, the vertical accuracies of these novel technologies are largely unverified thus standard and repeatable field procedures to validate remotely sensed WSE and WSS are needed. To that end, we designed, engineered and operationalized a Water Surface Profiler (WaSP) system that efficiently and accurately surveys WSE and WSS in a variety of surface water environments using Global Navigation Satellite Systems (GNSS) time-averaged measurements with Precise Point Positioning (PPP) corrections. Here, we present WaSP construction, deployment, and a data processing workflow. We demonstrate WaSP data collections from repeat field deployments in the North Saskatchewan River and three prairie pothole lakes near Saskatoon, Saskatchewan, Canada. We find that WaSP reproducibly measures WSE and WSS with vertical accuracies similar to standard field survey methods (WSE RMSD ~8 cm, WSS RMSD ~1.3 cm/km), and that repeat WaSP deployments accurately quantify water level changes (RMSD ~3 cm). Collectively, these results suggest that WaSP is an easily-deployed, self-contained system with sufficient accuracy for validating the decimeter level expected accuracies of SWOT and AirSWOT. We conclude by discussing the utility of WaSP for validating airborne and spaceborne WSE mappings, present 63 WaSP in-situ lake WSE measurements collected in support of NASA’s Arctic Boreal and Vulnerability Experiment (ABoVE), highlight routine deployment in support of the Lake Observation by Citizen Scientists and Satellites (LOCSS) project, and explore WaSP utility for validating a novel GNSS interferometric reflectometry (GNSS-IR) LArge Wave Warning System (LAWWS).

Fluctuations in water surface elevation (WSE) along rivers have important implications for water resources, flood hazards, and biogeochemical cycling. However, current in situ and remote sensing methods exhibit key limitations in characterizing spatiotemporal hydraulics of many of the world's river systems. Here, we analyze new measurements of river WSE and slope from AirSWOT, an airborne analogue to the Surface Water and Ocean Topography (SWOT) mission aimed at addressing limitations in current remotely sensed observations of surface water. To evaluate its capabilities, we compare AirSWOT WSEs and slopes to in situ measurements along the Tanana River, Alaska. RMSE is 9.0 cm for WSEs averaged over 1 km2 areas and 1.0 cm/km for slopes along 10 km reaches. Results indicate that AirSWOT can accurately reproduce the spatial variations in slope critical for characterizing reach-scale hydraulics. AirSWOT's high-precision measurements are valuable for hydrologic analysis, flood modeling studies, and for validating future SWOT measurements.

Extensive, complex supraglacial river networks form on the southwest Greenland ice sheet (GrIS) surface each melt season. These networks are the dominant pathways for surface meltwater transport on this part of the ice sheet, but their fluvial morphometry has received little study. This paper utilizes high-resolution (2 m) WorldView-1/2 images, digital elevation models, and GIS tools to present a detailed morphometric characterization (river number, river length, Strahler stream order, width, depth, bifurcation ratio, braiding index, drainage density, slope, and relief ratio) for 523 GrIS supraglacial river networks. A new algorithm is presented to determine Strahler stream order in supraglacial environments. Results show that (1) Supraglacial river networks are broadly similar to terrestrial landscapes in that they follow Horton’s laws (river number, mean river length, and slope versus stream order), widen downstream, and have comparable mean bifurcation ratios (3.7 ± 1.9) and braiding indices; (2) unlik...

Shade-grown coffee (shade coffee) is an important component of the forested tropics, and is essential to the conservation of forest-dependent biodiversity. Despite its importance, shade coffee is challenging to map using remotely sensed data given its spectral similarity to forested land. This paper addresses this challenge in three districts of northern Nicaragua, here leveraging cloud-based computing techniques within Google Earth Engine (GEE) to integrate multi-seasonal Landsat 8 satellite imagery (30 m), and physiographic variables (temperature, topography, and precipitation). Applying a random forest machine learning algorithm using reference data from two field surveys produced a 90.5% accuracy across ten classes of land cover, with an 82.1% and 80.0% user’s and producer’s accuracy respectively for shade-grown coffee. Comparing classification accuracies obtained from five datasets exploring different combinations of non-seasonal and seasonal spectral data as well as physiographic data also revealed a trend of increasing accuracy when seasonal data were included in the model and a significant improvement (7.8–20.1%) when topographical data were integrated with spectral data. These results are significant in piloting an open-access and user-friendly approach to mapping heterogeneous shade coffee landscapes with high overall accuracy, even in locations with persistent cloud cover.

Choice of watershed delineation technique is an important source of uncertainty for cryo-hydrologic studies of the Greenland Ice Sheet (GrIS), with different methods yielding different watersheds for a common pour point. First, this paper explores this uncertainty for the Akuliarusiarsuup Kuua River Northern Tributary, Western Greenland. Next, a standardized, semi-automated modeling framework for generating land-ice watersheds for GrIS land-terminating ice (henceforth referred to as CryoSheds) using geographic information systems (GIS) hydrologic modeling tools is presented. The framework uses ArcGIS and the ArcPy geoprocessing library to delineate two types of land-ice watersheds, namely those defined by: (1) a hydraulic pressure potential with varying water to ice overburden pressure ratios (k-value), which determines theoretical flow paths from the hydrostatic equation, using surface and bedrock digital elevation models (DEMs) and (2) a surface topography DEM alone. Lastly, a demonstration of the CryoSheds method is presented for seven remotely sensed proglacial pour points along the Aussivigssuit River (AR), Western Greenland, and its largest tributaries. GrIS meltwater runoff from these seven nested land-ice watersheds is estimated using Modele Atmospherique Regional (MAR) v.3.2 and runoff uncertainties due to watershed delineation parameter selection is estimated.