The monitoring of Earth's and planetary surface elevations at larger and finer scales is rapidly progressing through the increasing availability and resolution of digital elevation models (DEMs). Surface elevation observations are being used across an expanding range of fields to study topographical attributes and their changes over time, notably in glaciology, hydrology, volcanology, seismology, forestry and geomorphology. However, DEMs frequently contain large-scale instrument noise and varying vertical precision that lead to complex patterns of errors. Here, we present a validated statistical workflow to estimate, model, and propagate uncertainties in DEMs. We review the state-of-the-art of DEM accuracy and precision analyses, and define a conceptual framework to consistently address those. We show how to characterize DEM precision by quantifying the heteroscedasticity of elevation measurements, i.e. varying vertical precision with terrain-or sensor-dependent variables, and the spatial correlation of errors that can occur across multiple spatial scales. With the increasing availability of high-precision observations, our workflow based on independent elevation data acquired on stable terrain can be applied almost anywhere on Earth. We illustrate how to propagate uncertainties for both pixel-scale and spatial elevation derivatives, using terrain slope and glacier volume changes as examples. We find that uncertainties in DEMs are largely underestimated in the literature, and advocate that new metrics of DEM precision are essential to ensure the reliability of future Earth and planetary surface elevation assessments.

Permafrost and glaciers in the high Arctic form an impermeable ‘cryospheric cap’ that traps a large reservoir of subsurface methane, preventing it from reaching the atmosphere. Cryospheric vulnerability to climate warming is making releases of this methane possible. On Svalbard, where air temperatures are rising more than two times faster than the average for the Arctic, glaciers are retreating and leaving behind exposed forefields that enable rapid methane escape. Here we document how methane-rich groundwater springs have formed in recently revealed forefields of 78 land-terminating glaciers across central Svalbard, bringing deep-seated methane gas to the surface. Waters collected from these springs during February–May of 2021 and 2022 are supersaturated with methane up to 600,000 times greater than atmospheric equilibration. Spatial sampling reveals a geological dependency on the extent of methane supersaturation, with isotopic evidence of a thermogenic source. We estimate annual methane emissions from proglacial groundwaters to be up to 2.31 kt across the Svalbard archipelago. Further investigations into marine-terminating glaciers indicate future methane emission sources as these glaciers transition into fully land-based systems. Our findings reveal that climate-driven glacial retreat facilitates widespread release of methane, a positive feedback loop that is probably prevalent across other regions of the rapidly warming Arctic.

Abstract. Debris flows threaten communities in mountain regions worldwide. Combining modern photogrammetric processing with autonomous unoccupied aerial vehicle (UAV) flights at sub-weekly intervals allows mapping of sediment dynamics in a debris flow catchment. This provides important information for sediment disposition that pre-conditions the catchment for debris flow occurrence. At the Illgraben debris flow catchment in Switzerland, our autonomous UAV launched nearly 50 times in the snow-free periods in 2019–2021 with typical flight intervals of 2–4 d, producing 350–400 images every flight. The observed terrain changes resulting from debris flows exhibit preferred locations of erosion and deposition, including memory effects as previously deposited material is preferentially removed during subsequent debris flows. Such data are critical for the validation of geomorphological process models. Given the remote terrain, the mapped short-term erosion and deposition structures are difficult to obtain with conventional measurements. The proposed method thus fills an observational gap, which ground-based monitoring and satellite-based remote sensing cannot fill as a result of limited access, reaction time, spatial resolution, or involved costs.