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Knowing the extent of human influence on the global hydrological cycle is essential for the sustainability of freshwater resources on Earth1,2. However, a lack of water level observations for the world’s ponds, lakes and reservoirs has limited the quantification of human-managed (reservoir) changes in surface water storage compared to its natural variability3. The global storage variability in surface water bodies and the extent to which it is altered by humans therefore remain unknown. Here we show that 57 per cent of the Earth’s seasonal surface water storage variability occurs in human-managed reservoirs. Using measurements from NASA’s ICESat-2 satellite laser altimeter, which was launched in late 2018, we assemble an extensive global water level dataset that quantifies water level variability for 227,386 water bodies from October 2018 to July 2020. We find that seasonal variability in human-managed reservoirs averages 0.86 metres, whereas natural water bodies vary by only 0.22 metres. Natural variability in surface water storage is greatest in tropical basins, whereas human-managed variability is greatest in the Middle East, southern Africa and the western USA. Strong regional patterns are also found, with human influence driving 67 per cent of surface water storage variability south of 45 degrees north and nearly 100 per cent in certain arid and semi-arid regions. As economic development, population growth and climate change continue to pressure global water resources4, our approach provides a useful baseline from which ICESat-2 and future satellite missions will be able to track human modifications to the global hydrologic cycle. Data from the ICESat-2 satellite quantifying the variability of water levels in natural and human-managed water bodies show that a disproportionate majority of global water storage variability occurs in human-managed reservoirs.

Shorefast sea ice comprises only about 12% of global sea-ice cover, yet it has outsized importance for Arctic societies and ecosystems. Relatively little is known, however, about the dominant drivers of its breakup or how it will respond to climate warming. Here, we use 19 years of near-daily satellite imagery to document the timing of shorefast ice breakup in 28 communities in northern Canada and western Greenland that rely on shorefast ice for transportation and traditional subsistence activities. Breakup timing is strongly correlated with springtime air temperature, but the sensitivity of the relationship varies substantially among communities. We combine these observations with future warming scenarios to estimate an annual reduction of 5–44 days in the length of the springtime shorefast ice season by 2100. Paradoxically, the coldest communities are projected to experience the largest reductions in springtime ice season duration. Our results emphasize the local nature of climate change and its varied impacts on Arctic communities. Shorefast sea ice, which forms along the Arctic shore in winter and spring, is important for local communities and ecosystems. Satellite and climate model data are used to estimate a decrease in shorefast ice season length of 5–44 days by 2100, with the coldest areas experiencing the largest reductions.

We present a portable photon-counting LiDAR that uses a bistatic geometry to measure pulse broadening in the multiple-scattering regime. A diffusion model allows us to extract optical scattering and absorption coefficients of glacier ice.

Author(s): Durand, Michael; Barros, Ana; Dozier, Jeff; Adler, Robert; Cooley, Sarah; Entekhabi, Dara; Forman, Barton A; Konings, Alexandra G; Kustas, William P; Lundquist, Jessica D; Pavelsky, Tamlin M; Rodell, Matthew; Steele‐Dunne, Susan

The Greenland Ice Sheet’s contribution to global sea-level rise is accelerating1 due to increased melting of its bare-ice ablation zone2–6, but there is growing evidence that climate models overestimate runoff from this critical area of the ice sheet7–12. Current climate models assume all bare ice runoff escapes to the ocean, unlike snow covered areas where some fraction of runoff is retained and/or refrozen in porous firn13–15. Here we use in situ measurements and numerical modeling to reveal extensive retention and refreezing of liquid meltwater in bare glacial ice, explaining chronic runoff overestimation by climate models. From 2009–2018, refreezing of liquid meltwater in bare, porous glacial ice reduced meltwater runoff by 11–23 Gt a-1 in southwest Greenland alone, equivalent to 10–20% of annual meltwater production. This mass retention is commensurate with current estimates of climate model ice sheet meltwater runoff uncertainty, and may represent an overlooked buffer on projected runoff increases for the coming century16. Inclusion of bare-ice retention and refreezing processes in climate models therefore has immediate potential to improve forecasts of ice sheet runoff and its contribution to global sea-level rise.

Greenland ice sheet surface runoff is evacuated through supraglacial stream networks, which influence surface mass balance as well as ice dynamics. However, in-situ observations of meltwater discharge through these stream networks are rare. In this study, we present 46 discharge measurements and continuous water level measurements for 62 days spanning 13 June to 13 August 2016 for a 0.6 km2 supraglacial stream catchment in southwest Greenland. The result is an unprecedented long record of supraglacial discharge capturing both diurnal and seasonal variability. By comparing in situ hydraulic geometry parameters with previous studies, we find that significant heterogeneity exists such that estimating stream discharge using these parameters over ungauged supraglacial catchments could lead to substantial errors. A comparison of surface energy fluxes to stream discharge reveals shortwave radiation as the primary driver of melting (78 % of melt energy). However, during high melt episodes, the shortwave only contributes to 50 % of melt energy. Instead, the relative contribution of longwave radiation, sensible and latent heat fluxes to overall melt increases by 16.5 %, 4 %, and 7 % respectively. Our data also show a seasonal variation in the timing of daily maximum discharge during clear sky days, shifting from 16:00 local time (i.e., 2.75 hours after solar noon) in late June to 14:00 in late July, then rapidly returns to 16:00 in early August coincident with an abrupt drop in air temperature. These changes in peak daily flow timing can be attributed to a changing effective catchment area, resulting in a smaller stream network supplying water to the outlet at the end of the season throughout the melt season. Further work is needed to uncover how widespread rapid shift in the timing of peak discharge is across Greenland supraglacial streams, and thus their potential impact on meltwater delivery to the subglacial system and ice dynamics.

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).

Knowing the extent of human influence on the global hydrological cycle is essential for the sustainability of freshwater resources on Earth

S.W.C. acknowledges financial support from the Gates Cambridge Trust at the University of Cambridge. PC acknowledges funding from the European Research Council under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 683043).

Greenland’s snowline exhibits large fluctuations and is a primary amplifier of ice sheet surface melt and runoff., Greenland Ice Sheet mass loss has recently increased because of enhanced surface melt and runoff. Since melt is critically modulated by surface albedo, understanding the processes and feedbacks that alter albedo is a prerequisite for accurately forecasting mass loss. Using satellite imagery, we demonstrate the importance of Greenland’s seasonally fluctuating snowline, which reduces ice sheet albedo and enhances melt by exposing dark bare ice. From 2001 to 2017, this process drove 53% of net shortwave radiation variability in the ablation zone and amplified ice sheet melt five times more than hydrological and biological processes that darken bare ice itself. In a warmer climate, snowline fluctuations will exert an even greater control on melt due to flatter ice sheet topography at higher elevations. Current climate models, however, inaccurately predict snowline elevations during high melt years, portending an unforeseen uncertainty in forecasts of Greenland’s runoff contribution to global sea level rise.

The annual spring breakup of river ice has important consequences for northern ecosystems and significant economic implications for Arctic industry and transportation. River ice breakup research is restricted by the sparse distribution of hydrological stations in the Arctic, where limited available data suggests a trend towards earlier ice breakup. The specific climatic mechanisms driving this trend, however, are complex and can vary both regionally and within river systems. Consequently, understanding the response of river ice processes to a warming Arctic requires simultaneous examination of spatial and temporal patterns in breakup timing. In this paper, we describe an automated algorithm for river ice breakup detection using MODIS satellite imagery that enables identification of spatial and temporal breakup patterns at large scales. We examine breakup timing on the Mackenzie, Lena, Ob' and Yenisey rivers for the period 2000–2014. By dividing the rivers into 10 km segments and classifying each river pixel in each segment as snow/ice, mixed ice/water or open water based on MODIS reflectance, we determine breakup dates with a mean uncertainty of ± 1.3 days. All statistically significant temporal trends are negative, indicating an overall shift towards earlier breakup. Considerable variability in the statistical significance and magnitude of trends along each river suggests that different climatic and physiographic drivers are impacting spatial patterns in breakup. Trends detected on the lower Mackenzie corroborate recent studies indicating weakening ice resistance and earlier breakup timing near the Mackenzie Delta. In Siberia, the increased magnitude of trends upstream and strong correlation between breakup initiation and whole-river breakup patterns suggest that earlier onset of upstream discharge may play the dominant role in determining breakup timing. Exploratory analysis demonstrates that MODIS imagery may also be used to differentiate thermal and mechanical breakup events.

AirSWOT is an experimental airborne Ka-band radar interferometer developed by NASA-JPL as a validation instrument for the forthcoming NASA Surface Water and Ocean Topography (SWOT) satellite mission. In 2017, AirSWOT was deployed as part of the NASA Arctic Boreal Vulnerability Experiment (ABoVE) to map surface water elevations across Alaska and western Canada. The result is the most extensive known collection of near-nadir airborne Ka-band interferometric synthetic aperture radar (InSAR) data and derivative high-resolution (3.6 m pixel) digital elevation models to produce water surface elevation (WSE) maps. This research provides a synoptic assessment of the 2017 AirSWOT ABoVE dataset to quantify regional WSE errors relative to coincident in situ field surveys and LiDAR data acquired from the NASA Land, Vegetation, and Ice Sensor (LVIS) airborne platform. Results show that AirSWOT WSE data can penetrate cloud cover and have nearly twice the swath-width of LVIS as flown for ABoVE (3.2 km vs. 1.8 km nominal swath-width). Despite noise and biases, spatially averaged AirSWOT WSEs can be used to estimate sub-seasonal hydrologic variability, as confirmed with field GPS surveys and in situ pressure transducers. This analysis informs AirSWOT ABoVE data users of known sources of measurement error in the WSEs as influenced by radar parameters including incidence angle, magnitude, coherence, and elevation uncertainty. The analysis also provides recommended best practices for extracting information from the dataset by using filters for these four parameters. Improvements to data handing would significantly increase the accuracy and spatial coverage of future AirSWOT WSE data collections, aiding scientific surface water studies, and improving the platform’s capability as an airborne validation instrument for SWOT.

We document the density and hydrologic properties of bare, ablating ice in a mid-elevation (1215 m a.s.l.) supraglacial internally drained catchment near Kangerlussuaq, southwest Greenland. We find water saturated, low-density (474–725 kg m −3 , μ = 688 kg m −3 ) ice to at least 1.1 m depth below the ice sheet surface. This near surface, low-density ice consists of alternating fractured porous ice and clear solid ice lenses, overlain by a thin ( −3 , μ = 455 kg m −3 ) unsaturated weathering crust. Ice-density data from 10 shallow (0.9–1.1 m) ice cores along an 800 m transect suggest an average 15–22 cm of liquid meltwater storage within this low-density ice. Water saturation of this ice is confirmed through measurable water levels (1–29 cm, μ = 10 cm) in 84 % of cryoconite holes and rapid infilling of 83 % of 1 m drilled holes sampled along the transect. Though preliminary, these findings are consistent with descriptions of shallow, depth-limited aquifers in weathering crusts of temperate and polythermal glaciers worldwide, and confirm the potential for substantial transient meltwater storage within porous low-density ice on the Greenland Ice Sheet ablation zone surface. A conservative estimate for the ~ 63 km 2 catchment yields 0.010–0.014 km 3 of liquid meltwater storage in near-surface, low-density ice. Further work is required to determine whether these findings are representative of broader areas of the Greenland Ice Sheet ablation zone, and to assess the implications for sub-seasonal surface mass balance calculations, surface lowering observations from airborne and satellite altimetry, and supraglacial runoff processes.

Recent deployments of CubeSat imagers by companies such as Planet may advance hydrological remote sensing by providing an unprecedented combination of high temporal and high spatial resolution imagery at the global scale. With approximately 170 CubeSats orbiting at full operational capacity, the Planet CubeSat constellation currently offers an average revisit time of