ABSTRACT Pingos and related permafrost mounds are widespread periglacial landforms in Arctic environments that are ice‐rich on the one hand and contain taliks on the other, making them vulnerable to climate change. So far, the interior, geophysical characteristics, and distribution of ground ice within these dome‐ or cone‐shaped features have not been sufficiently investigated, and more in situ observations and multidimensional insights are required. This study presents two‐ and three‐dimensional Electrical Resistivity Tomography (ERT) results from numerous pingos and permafrost mounds investigated in the Ogilvie Mountains and on the Tuktoyaktuk Peninsula, northwest Canada. The measurements cover single features and assemblages of varying sizes and shapes, in mountain valleys, on slopes and at riversides, in drained lakes, and at lakeshores. Resistivities are compared based on representative zones of interest within 2D profiles, and large quasi‐3D grids were set up to test the capabilities of 2D ERT and especially 3D ERT for the investigation of pingos and permafrost mounds. Using this data, the study helps to decipher the origin and development of the landforms, exemplified for specific sites in mountainous vs. coastal environments by additionally considering their complex hydrological settings. The pingos reveal median interior electrical resistivities of 5–50 kΩm, and all have maximum resistivities exceeding 10 kΩm. The bigger ones feature cores of far beyond 100 kΩm, which contrasts with the often more conductive interiors of smaller or different types of permafrost mounds. Difficulties arise when deriving a common resistivity threshold for massive pingo ice. ERT is a powerful tool to three‐dimensionally display the interior of pingos, to detect potential talik areas, and to help to distinguish pingos from other mound landforms based on geoelectrical properties. It enables the estimation of the upper limit and the lateral extent of massive ice cores, but in many cases struggles to provide reliable information on structures below massive ice. Investigating pingos using ERT, therefore, requires careful evaluation of the model sensitivity. The ERT findings and hydrological discussion underline the probable co‐existence of hydraulic and hydrostatic pingos in mountain valleys, and reveal similar characteristics and positions of permafrost mounds as of open‐system pingos. However, the position, lateral extent, and electrical properties of internal massive ice vary between sites and even within single assemblages. Specifically, within the biggest investigated pingo on the Tuktoyaktuk Peninsula, the extent of the detected ice core hardly explains the size and surface appearance of the landform, whereas conductive, likely unfrozen or solute‐rich pockets in the flanks cause an even more heterogeneous internal structure. The investigated examples paint a much more complex picture of the pingo architecture and genesis than traditional models have suggested to date.
ABSTRACT Understanding fine‐scale surface changes is crucial for quantifying ecosystem dynamics and detecting landscape changes. Palsas, comparably small peatland elevations with an ice‐rich permafrost core, undergo natural cycles of growth and degradation. They can also serve as indicators of climate change in subarctic regions. Because they typically cover an area of only a few hundred square metres at most, satellite remote sensing is insufficient for monitoring their detailed development. Unoccupied aerial systems (UAS) and ground‐based remote sensing provide the necessary spatial resolution, and combining multiple sensor types can further improve data quality. In this study, we monitored the annual surface changes of two degrading palsas in northern Finnish Lapland from 2022 to 2024. We captured UAS RGB‐based structure‐from‐motion (SfM), UAS LiDAR and terrestrial laser scanning (TLS) point clouds and validated the resulting digital terrain models (DTMs) using RTK‐GNSS reference measurements. Active layer thickness (ALT) was measured at each GNSS point to characterize thaw depth and to delineate an ALT‐constrained frozen extent. Based on the DTMs, we quantified changes in palsa area, mean height, and volume above a predefined palsa base. These DTM‐based metrics were evaluated for the entire palsa surface and, separately, for the part of the palsa where ALT measurements indicated the presence of a remaining frozen core. The accuracy assessment shows clear advantages of merging SfM point clouds with LiDAR‐ or TLS‐derived datasets. The highest accuracy was achieved at the smaller and flatter palsa, suggesting that high point cloud density and low surface complexity increase accuracy. UAS LiDAR showed a consistent positive elevation bias, likely reflecting a combination of slope‐ and footprint‐related effects and limited penetration of moist moss and peat surfaces. Both palsas lost volume, area and average height during the study period. The larger palsa decreased in total volume by 20% across its entire extent and by 23% within the ALT‐constrained frozen extent; the smaller palsa lost 13% and 18%, respectively. These results underscore the acceleration of palsa degradation under current climatic conditions and demonstrate that multisensor approaches significantly improve high‐resolution monitoring of palsa surface change in permafrost landscapes.
ABSTRACT Pingos are large mounds with cores formed of intrusive ice that form in periglacial landscapes. These ice structures can form in regions of discontinuous permafrost, commonly as hydraulic or open‐system pingos, or in locations of continuous permafrost, commonly as hydrostatic or closed‐system pingos. Using C‐band Interferometric Synthetic Aperture Radar (InSAR) data from the Sentinel‐1 constellation acquired between 2017 and 2025 over the Alaskan North Slope, we quantified interannual surface deformation trends over several hydrostatic pingos. Eight of the 11 pingos analyzed experienced cumulative uplift ranging from 1.49 to 11.35 cm over an 8‐year period, two experienced cumulative subsidence ranging from 0.57 to 2.46 cm, and two experienced no statistically significant surface‐height change. All of the cumulatively uplifting pingos exhibited surface‐height time series proportional to a square‐root dependence with time, which is physically consistent with an aggradational process via Stefan's equation. Ground penetrating radar profiles acquired over select pingos revealed subsurface reflector structures consistent with massive ice cores, reinforcing the hypothesis that the observed surface uplift is driven by intrusive ice formation mediated by elevated hydrostatic pressure due to permafrost aggradation. These results demonstrate that InSAR methods can resolve subtle geodetic signals associated with pingo topographic change, such as from pingo growth due to permafrost aggradation. InSAR observations can thus yield process‐scale insights into the dynamic evolution of pingos and associated periglacial landforms.
Freeze-thaw processes cause periglacial creep (otherwise known as solifluction) which forms solifluction lobes. These are lobate features characterized by a steep riser (front) and a smooth tread (body). Despite the widespread occurrence of these lobes, the controls on their morphometry remain poorly understood. Research into solifluction lobe morphometry is crucial for understanding their role in landscape evolution, hydrology and sediment budgets and providing microhabitats in a warming climate. We mapped geomorphic and vegetation properties of 40 solifluction lobes in the Turtmann Valley, Swiss Alps, and recorded soil moisture and temperature with a TOMST TMS4 logger at a 10-min interval for nearly 2 years. We combined these data with derivatives of a high-resolution digital elevation model and conducted a Spearman ranked correlation test. Our results revealed that (i) the largest lobes, with the highest risers occur in areas with high flow accumulation (rho = 0.40-0.75). (ii) Wider, lobate lobes dominate at higher elevations (rho = 0.49) on north-exposed slopes (rho = 0.53) with long snow (rho = 0.47-0.58) and sparse vegetation cover, while narrow, tongue-shaped lobes occur at lower elevations with high vegetation cover (rho = 0.38-0.55), suggesting a strong topoclimatic control. (iii) Lobes in the Turtmann Valley are longer and more tongue-shaped, with higher risers and on steeper slopes, than many lobes previously studied. Overall, our results suggest that Alpine solifluction lobe dimensions and shape are controlled by different set of environmental factors than Arctic lobes, possibly due to effects of stronger topoclimatic gradients, steeper slopes and higher flow accumulation on mountain slopes.
Due to its subsurface nature, permafrost cannot be directly observed with the naked eye or optical remote sensing. Consequently, accurately describing its distribution and thermal state is challenging. This is especially true in vast, remote environments, where obtaining comprehensive field data is demanding or improbable. This results in a reliance on models, which are constrained by limited, spatiotemporally fragmented baseline data, and which are rarely validated against actual field data. While such models may be sufficient in homogeneous permafrost environments, or to capture general trends over large areas, their accuracy is limited at finer scales in thermally heterogeneous environments. To explore and conceptualize this issue, we conducted a field sampling campaign in two thermally complex valleys in the Ogilvie Mountains. The study area exhibits strong ground temperature variability over short distances due to surface-based temperature inversions, extreme aspects, and complex land cover types. Our objective was to qualitatively assess our ability to collect in situ permafrost thermal data ("testability") using simple, repeatable, low-cost methods. Although the study area is located within the zone of continuous permafrost, only nine (18.3%) of the 49 Cryotic Assessment Sites (CAS) produced cryotic temperatures in situ, due to substrate clast density and active layer thickness. Testability outcomes were used to develop a generalized linear model (P TEST), which predicts low testability at higher elevations and higher testability in valley bottoms, indicating a substantial potential sampling bias for model calibration and validation. Comparisons with two local permafrost models highlight persistent uncertainty in permafrost characterization in mountainous environments.
