Richard R. Forster

Interferometric Synthetic Aperture Radar (InSAR) offers a potential pathway for measuring seasonal snow water equivalent (SWE) and snow depth at spatial and temporal scales needed for basin‐scale hydrology. First proposed for seasonal snow more than 25 years ago, InSAR uses repeat‐pass radar phase differences to estimate changes in SWE or depth caused by microwave propagation through snow. This review synthesizes InSAR‐based snow monitoring from early theoretical and satellite demonstrations through recent tower, airborne, and spaceborne studies. We summarize the retrieval physics, evaluate published validation results, compare performance across wavelengths and snow environments, and identify barriers to operational implementation. The literature shows that InSAR can provide high‐resolution, spatially distributed information on snow accumulation and ablation, especially under dry‐snow conditions when temporal coherence is maintained and snow phase can be separated from atmospheric, vegetation, soil‐moisture, and other non‐snow contributions. Longer wavelengths, particularly L‐band, help maintain coherence, reduce phase‐wrapping ambiguity, and support retrievals in some vegetated environments, making the NASA–ISRO Synthetic Aperture Radar (NISAR) mission a timely opportunity for basin‐scale testing. Remaining challenges include correcting ionospheric and tropospheric delays; defining stable reference phases; identifying, correcting, or flagging coherence loss and phase‐unwrapping errors; accounting for forest‐canopy interactions; collecting spatially distributed validation data; and scaling site demonstrations to regional or global products. Operational use will require algorithmic maturation, robust validation, and integration with other remote sensing and modeling approaches. If these challenges are addressed, InSAR‐capable satellites could become an important component of an integrated global snow observation suite.

Field‐based studies are limited in Himalaya‐Karakoram (HK); therefore, remote sensing and glaciohydrological modeling provide alternative solutions to investigate runoff evolution under changing climate conditions. Due to limited in situ runoff data in HK, glaciohydrological models are often calibrated using high‐resolution remote sensing data. This study introduces the calibration of the glaciohydrological model Spatial Processes in Hydrology (SPHY), at glacier catchment‐scale over 2000–2023 using satellite‐based Sentinel‐1 Synthetic Aperture Radar (SAR) wet snow maps, along with available geodetic mass balance estimates in the HK region. The selected calibrated model parameters are validated against in situ runoff data to test the robustness of satellite‐based calibration for Chhota Shigri Glacier (CSG), Dokriani Bamak Glacier (DBG), and Gangotri Glacier System (GGS) catchments in HK. The SPHY modeled and in situ catchment‐wide runoff estimates show good agreement. The Sentinel‐1 SAR‐derived wet snow percentage area shows strong spatial and temporal variability from 2015 to 2023. The mean annual runoff is 1.79 ± 0.15 m ³ s ⁻¹ , 1.63 ± 0.09 m ³ s ⁻¹ and 39.40 ± 3.15 m ³ s ⁻¹ over 2000–2023 for CSG, DBG and GGS catchments, respectively. Maximum annual runoff occurred in 2021/2022, mainly due to heatwaves in early spring/summer 2022. Snowmelt runoff is highest in CSG (61%) and GGS (49%), while rainfall‐runoff dominates in DBG (42%). Satellite‐based glaciohydrological model calibration offers a unique opportunity to improve runoff estimates for glacierized catchments in data‐sparse regions. Applying present study to glacierized catchments lacking in situ runoff data will strengthen our past, present, and future glaciohydrological understanding of regions such as HK and Andes.

This work contains educational modules designed to reduce barriers to interacting with large, complex, cloud-hosted remote sensing datasets using open-source computational tools and software. The goal of these materials is to demonstrate and promote the rigorous investigation of n-dimensional multi-sensor satellite imagery datasets through scientific programming. These tutorials feature publicly available satellite imagery with global coverage and commonly used sensors such as optical and synthetic aperture radar data with different levels of processing. We include thorough discussions of specific data formats and demonstrate access patterns for two popular cloud infrastructure platforms (Amazon Web Services and Microsoft Planetary Computer) as well as public cloud computational resources for remote sensing data processing at Alaska Satellite Facility (ASF).

Upper Indus Basin (UIB) streamflow originates largely from glacier and snow melt in the upstream Himalaya, Karakoram, and Hindu Kush mountain ranges and is extremely vulnerable because of its projected climate changes, dense populations, and hydropolitical tensions. Accurate knowledge of streamflow constituents is required for resilient water resources management; this is precluded by a paucity of measurement as well as climatological and topographic complexity. Here we integrate citizen scientist acquired geochemical samples, collected from October 2018 through September 2019 in the Shimshal watershed of the Karakoram Mountains of Pakistan, with Sentinel‐1 (S1) synthetic aperture radar (SAR)‐derived wet snow maps, to better understand streamflow constituents for the high altitude and heavily glaciated catchment. We use Bayesian end‐member mixture analysis to separate river flows into baseflow and meltwater constituents, using fixed and time‐variant melt end‐member values. We compare river hydrograph separation results with S1 wet snow time series maps for the same timeframe. We then utilize S1 imagery to inform end‐member mixture analysis to separate meltwaters into snow and glacier melt. For the Shimshal catchment, we find that about 85% of annual river flows are derived from snow and glacier melt; 45% of annual flows are derived from snow melt and 40% glacier melt. Engaged and committed citizen scientists enabled geochemical sample collection and analysis on a significant temporal and spatial scale. In the future, co‐produced knowledge that both implements local expertise and that is also planned and utilized by diverse stakeholders may increase climatological awareness and resilience in the UIB.

We present measurements of the density, hydraulic conductivity, and specific discharge of a widespread firn aquifer in Antarctica, within the Wilkins Ice Shelf. At the field site, the aquifer is 16.2 m thick, starting at 13.4 m from the snow surface and transitioning from water‐saturated firn to ice at 29.6 m. Hydraulic conductivity derived from slug tests show a geometric mean value of 1.4 ± 1.2 × 10⁻⁴ m s⁻¹, equivalent to permeability of 2.6 ± 2.2 × 10⁻¹¹ m². A borehole dilution test indicates an average specific discharge value of 1.9 ± 2.8 × 10⁻⁶ m s⁻¹. Ground‐penetrating radar profiles and a groundwater flow model show the aquifer is draining laterally into a large nearby rift. Our findings indicate that the firn aquifer in the vicinity of the field site is likely not in a steady state and its presence likely contributed to past ice shelf instability.

Perennial water storage in firn aquifers has been observed within the lower percolation zone of the southeast Greenland ice sheet. Spatially distributed seismic and radar observations, made ~50 km upstream of the Helheim Glacier terminus, reveal spatial variations of seismic velocity within a firn aquifer. From 1.65 to 1.8 km elevation, shear‐wave velocity (Vs) is 1,290 ± 180 m/s in the unsaturated firn, decreasing below the water table (~15 m depth) to 1,130 ± 250 m/s. Below 1.65 km elevation, Vs in the saturated firn is 1,270 ± 220 m/s. The compressional‐to‐shear velocity ratio decreases in the downstream saturated zone, from 2.30 ± 0.54 to 2.01 ± 0.46, closer to its value for pure ice (2.00). Consistent with colocated firn cores, these results imply an increasing concentration of ice in the downstream sites, reducing the porosity and storage potential of the firn likely caused by episodic melt and freeze during the evolution of the aquifer.

Firn aquifers have been discovered across regions of the Greenland ice sheet with high snow accumulation and melt rates, but the processes and rates that sustain these aquifers have not been fully quantified or supported by field data. A quantitative description of the hydrology of a firn aquifer upslope from Helheim Glacier that integrates field measurements is presented to constrain melt and recharge rates and timing, temporal variations in temperature and water levels, and liquid‐water residence time. Field measurements include weather data, firn temperatures, water levels, geochemical tracers, and airborne radar data. Field measurements show that once the firn column is temperate (0°C), meltwater from the surface infiltrates to the water table in less than 2 days and raises the water table. Average recharge is 22 cm/year (lower 95% confidence interval is 13 cm/year and upper 95% confidence interval is 33 cm/year). Meltwater within the recently formed aquifer, which flows laterally downslope and likely discharges into crevasses, has a mean residence time of ~6.5 years. Airborne radar data suggest that the aquifer in the study area continues to expand inland, presumably from Arctic warming. These comprehensive field measurements and integrated description of aquifer hydrology provide a comprehensive, quantitative framework for modeling fluid flow through firn, and understanding existing and yet undiscovered firn aquifers, and may help researchers evaluate the role of firn aquifers in climate change impacts.

Meltwater runoff from the Greenland Ice Sheet (GrIS) significantly contributes to sea level rise and is the dominant driver of enhanced mass loss. While most melt occurs during summer, little is known about its seasonal and/or interannual retention within the GrIS. Here, we document evidence of runoff during winter, ~4 months after summer melt. Ground‐penetrating radar and borehole surveys in the proglacial Isortoq River reveal slowly flowing water beneath >0.5 m of river ice. Geochemical analysis of this water indicates previous contact with the ice sheet bed. Comparable surveys in proglacial rivers draining four neighboring catchments found no winter drainage, despite a brief surface melt event ~10 days prior. We attribute the observed runoff to residual meltwater storage and release enabled by a >600 m deep trough beneath Isunguata Sermia, but not neighboring glaciers. We conclude that the GrIS bed can stay wet and drain small amounts of meltwater year‐round.

We document the existence of widespread firn aquifers in an elevation range of ~1200–2000 m, in the high snow‐accumulation regions of the Greenland ice sheet. We use NASA Operation IceBridge accumulation radar data from five campaigns (2010–2014) to estimate a firn‐aquifer total extent of 21,900 km². We investigate two locations in Southeast Greenland, where repeated radar profiles allow mapping of aquifer‐extent and water table variations. In the upper part of Helheim Glacier the water table rises in spring following above‐average summer melt, showing the direct firn‐aquifer response to surface meltwater production changes. After spring 2012, a drainage of the firn‐aquifer lower margin (5 km) is inferred from both 750 MHz accumulation radar and 195 MHz multicoherent radar depth sounder data. For 2011–2014, we use a ground‐penetrating radar profile located at our Ridgeline field site and find a spatially stable aquifer with a water table fluctuating less than 2.5 m vertically. When combining radar data with surface topography, we find that the upper elevation edge of firn aquifers is located directly downstream of locally high surface slopes. Using a steady state 2‐D groundwater flow model, water is simulated to flow laterally in an unconfined aquifer, topographically driven by ice sheet surface undulations until the water encounters crevasses. Simulations suggest that local flow cells form within the Helheim aquifer, allowing water to discharge in the firn at the steep‐to‐flat transitions of surface topography. Supported by visible imagery, we infer that water drains into crevasses, but its volume and rate remain unconstrained.