Soil erosion poses a considerable threat to ecosystem services around the world. Among these, it is extremely problematic for archaeological sites, particularly in arable landscapes where accelerated soil degradation has been widely observed. Conversely, some archaeological deposits may obtain a certain level of protection when they are covered by eroded material, thereby lessening the impacts of phenomena such as plow damage or bioturbation. As a result, detailed knowledge of the extent of colluvial deposition is of great value to site management and the development of appropriate methodological strategies. This is particularly true of battlefield sites, where the integrity of artifacts in the topsoil is of great importance and conventional metal detection (with its shallow depth of exploration) is relied upon as the primary method of investigation. Using the Napoleonic battlefield of Waterloo in Belgium as a case study, this paper explores how different noninvasive datasets can be combined with ancillary data and a limited sampling scheme to map colluvial deposits in high resolution and at a large scale. Combining remote sensing, geophysical, and invasive sampling datasets that target related phenomena across spatial scales allows for overcoming some of their respective limitations and derives a better understanding of the extent of colluvial deposition.

Slope failures are an ongoing global threat leading to significant numbers of fatalities and infrastructure damage. Landslide impact on communities can be reduced using efficient early warning systems to plan mitigation measures and protect elements at risk. This manuscript presents an innovative geophysical approach to monitoring landslide dynamics, which combines electrical resistivity tomography (ERT) and low-frequency distributed acoustic sensing (DAS), and was deployed on a slope representative of many landslides in clay rich lowland slopes. ERT is used to create detailed, dynamic moisture maps that highlight zones of moisture accumulation leading to slope instability. The link between ERT derived soil moisture and the subsequent initiation of slope deformation is confirmed by low-frequency DAS measurements, which were collocated with the ERT measurements and provide changes in strain at unprecedented spatiotemporal resolution. Auxiliary hydrological and slope displacement data support the geophysical interpretation. By revealing critical zones prone to failure, this combined ERT and DAS monitoring approach sheds new light on landslide mechanisms. This study demonstrates the advantage of including subsurface geophysical monitoring techniques to improve landslide early warning approaches, and highlights the importance of relying on observations from different sources to build effective landslide risk management strategies.

Arctic regions are highly impacted by the global temperature rising and its consequences and influences on the thermo-hydro processes and their feedbacks. Theses processes are especially not very well understood in the context of river-permafrost interactions and permafrost degradation. This paper focuses on the thermal characterization of a river-valley system in a continuous permafrost area (Syrdakh, Yakutia, Eastern Siberia) that is subject to intense thawing, with major consequences on water resources and quality. We investigated this Yakutian area through two transects crossing the river using classical tools such as in-situ temperature measurements, direct active layer thickness estimations, unscrewed aerial vehicle (UAV) imagery, heat transfer numerical experiments, Ground-Penetrating Radar (GPR), and Electrical Resistivity Tomography (ERT). Of these two transects, one was closely investigated with a long-term temperature time series from 2012 to 2018, while both of them were surveyed by geophysical and UAV data acquisition in 2017 and 2018. Thermodynamical numerical simulations were run based on the long-term temperature series and are in agreement with river thermal influence on permafrost and active layer extensions retrieved from GPR and ERT profiles. An electrical resistivity-temperature relationship highlights the predominant role of water in such a complicated system and paves the way to coupled thermo-hydro-geophysical modeling for understanding permafrost-river system evolution.

Climate warming has significantly changed the near-surface soil freeze state, significantly impacting terrestrial ecosystems and regional agroforestry production. As Northeast China (NEC) is highly sensitive to climate change, this study introduces the concept of velocity to analyze the spatial pattern of frozen days (F-DAY), onset date of soil freeze (F-ON), offset date of soil freeze (F-OFF), and number of soil freeze/thaw cycles in spring (F-TC) in NEC from 1979 to 2020. We observed that the velocity changes of F-DAY, F-ON, and F-TC in croplands were significantly higher than those in forests (difference > 1 km yr(-1)), with the fastest velocity changes found in the cropland of the Songnen Plain. The highest velocity of FOFF was found in the forests of the Greater Khingan Range. In most study areas (> 60%), the isoline of F-DAY/F-ON/F-OFF/F-TC showed a northward movement. The isoline of F-DAY/F-ON/F-OFF/ F-TC moved in the cold direction in each cropland region (Sanjiang, Songnen, and Liaohe River Plains) and forest regions (Greater Khingan and Lesser Khingan Ranges, and the Changbai Mountains). The results of the quantitative analysis indicate that air temperature (T-A) had a more significant effect on the velocity change of F-DAY and F-ON in cropland, whereas snowpack is the dominant factor in forests. In both forests and croplands, the main factor affecting the velocity of F-OFF was snowpack, and T(A )mainly affected the F-TC. This study is significant for formulating regional climate change countermeasures and maintaining ecological security in cold regions.

Global warming may result in increased polar amplification, but future temperature changes under different climate change scenarios have not been systematically investigated over Antarctica. An index of Antarctic amplification (AnA) is defined, and the annual and seasonal variations of Antarctic mean temperature are examined from projections of the Coupled Model Intercomparison Project Phase 6 (CMIP6) under scenarios SSP119, SSP126, SSP245, SSP370 and SSP585. AnA occurs under all scenarios, and is strongest in the austral summer and autumn, with an AnA index greater than 1.40. Although the warming over Antarctica accelerates with increased anthropogenic forcing, the magnitude of AnA is greatest in SSP126 instead of in SSP585, which may be affected by strong ocean heat uptake in high forcing scenario. Moreover, future AnA shows seasonal difference and regional difference. AnA is most conspicuous in the East Antarctic sector, with the amplification occurring under all scenarios and in all seasons, especially in austral summer when the AnA index is greater than 1.50, and the weakest signal appears in austral winter. Differently, the AnA over West Antarctica is strongest in austral autumn. Under SSP585, the temperature increase over the Antarctic Peninsula exceeds 0.5 degrees C when the global average warming increases from 1.5 degrees C to 2.0 degrees C above pre-industrial levels, except in the austral summer, and the AnA index in this region is strong in the austral autumn and winter. The projections suggest that the warming rate under different scenarios might make a large difference to the future AnA.

Greenhouse gases (GHGs) released from permafrost regions may have a positive feedback to climate change, but there is much uncertainty about additional warming from the permafrost carbon cycle. One of the main reasons for this uncertainty is that the observation data of large-scale GHG concentrations are sparse, especially for areas with rapid permafrost degradation. We selected the Mongolian Plateau as the study area. We first analyzed the active layer thickness and ground temperature changes using borehole observations. Based on ground observation data, we assessed the applicability of Greenhouse Gases Observing Satellite (GOSAT) carbon dioxide (CO2) and methane (CH4) datasets. Finally, we analyzed the temporal and spatial changes in near-surface CO2 and CH4 concentrations from 2010 to 2017 and their patterns in different permafrost regions. The results showed that the Mongolian permafrost has been experiencing rapid degradation. The annual average near-surface CO2 concentration increased gradually between 2.19 ppmv/yr and 2.38 ppmv/yr, whereas the near-surface CH4 concentration increased significantly from 7.76 ppbv/yr to 8.49 ppbv/yr. There were significant seasonal variations in near-surface CO2 and CH4 concentrations for continuous, discontinuous, sporadic, and isolated permafrost zones. The continuous and discontinuous permafrost zones had lower near-surface CO2 and CH4 concentrations in summer and autumn, whereas sporadic and isolated permafrost zones had higher near-surface CO2 and CH4 concentrations in winter and spring. Our results indicated that climate warming led to rapid permafrost degradation, and carbon-based GHG concentrations also increased rapidly in Mongolia. Although, GHG concentrations increased at rates similar to the global average and many factors can account for their changes, GHG concentration in the permafrost regions merits more attention in the future because the spatiotemporal distribution has indicated a different driving force for regional warming. (C) 2021 Elsevier B.V. All rights reserved.

The impact of permafrost thaw on hydrologic, thermal, and biotic processes remains uncertain, in part due to limitations in subsurface measurement capabilities. To better understand subsurface processes in thermokarst environments, we collocated geophysical and biogeochemical instruments along a thaw gradient between forested permafrost and collapse-scar bogs at the Alaska Peatland Experiment site near Fairbanks, Alaska. Ambient seismic noise monitoring provided continuous high-temporal resolution measurements of water and ice saturation changes. Maps of seismic velocity change identified areas of large summertime velocity reductions nearest the youngest bog, indicating potential thaw and expansion at the bog margin. These results corresponded well with complementary borehole nuclear magnetic resonance measurements of unfrozen water content with depth, which showed permafrost soils nearest the bog edges contained the largest amount of unfrozen water along the study transect, up to 25% by volume. In situ measurements of methane within permafrost soils revealed high concentrations at these bog-edge locations, up to 30% soil gas. Supra-permafrost talik zones were observed at the bog margins, indicating talik formation and perennial liquid water may drive lateral bog expansion and enhanced permafrost carbon losses preceding thaw. Comparison of seismic monitoring with wintertime surface carbon dioxide fluxes revealed differential responses depending on time and proximity to the bogs, capturing the controlling influence of subsurface water and ice on microbial activity and surficial emissions. This study demonstrates a multidisciplinary approach for gaining new understanding of how subsurface physical properties influence greenhouse gas production, emissions, and thermokarst development.

The acceleration of permafrost thaw due to warming, wetting, and disturbance is altering circumpolar landscapes. The effect of thaw is largely determined by ground ice content in near-surface permafrost, making the characterization and prediction of ground ice content critical. Here we evaluate the spatial and stratigraphic variation of near-surface ground ice characteristics in the dominant forest types in the North Slave region near Yellowknife, Northwest Territories, Canada. Physical variation in the permafrost was assessed through cryostructure, soil properties, and volumetric ice content, and relationships between these parameters were determined. Near-surface ground ice characteristics were contrasted between forest types. In black spruce forests the top of the permafrost was ice-rich and characterized by lenticular and ataxitic cryostructures, indicating the presence of an intermediate layer. Most white spruce/birch forests showed similar patterns; however, an increase in the active layer thickness and permafrost thaw at some sites have eradicated the transition zone, and the large ice lenses encountered at depth reflect segregated ground ice developed during initial downward aggradation of permafrost. Our findings indicate that white spruce/birch terrain will be less sensitive than black spruce forests to near-surface permafrost thaw. However, if permafrost thaws completely, white spruce/birch terrain will probably be transformed into wetland-thaw lake complexes due to high ground ice content at depth.

The subsurface structure of permafrost is of high significance to forecast landscape dynamics and the engineering stability of infrastructure under human impacts and climate warming, which is a modern challenge for Arctic communities. Application of the non-destructive method of geo-penetrating radar (GPR) survey is a promising way to study it. The study program, which could be used for planning and monitoring of measures of adaptation of Arctic communities to environmental changes is provided in this paper. The main principle was to use etalons of coupled radargrams and archive geological data to interpret changes in the permafrost structure from a grid of 5-10 m deep GPR transects. Here, we show the application of GPR to reconstruct and predict hazards of activation of cryogenic processes from the spatial variability in the structure of permafrost. The cumulative effects of the village and climate change on permafrost were manifested in changes in the active layer thickness from 0.5-1.0 m to up to 3.5 m. Despite that the permafrost degradation has declined due to the improved maintenance of infrastructure and the effects of ground filling application, the hazards of heaving and thermokarst remain for the built-up area in Lorino.

Surface temperature is critical for the simulation of climate change impacts on the ecology, environment, and particularly permafrost in the cryosphere. Virtually, surface temperatures are different in the near-surface air temperature (T-a) measured at a screen-height of 1.5-2 m, the land surface temperature (LST) on the top canopy layer, and the ground surface temperature (GST) 0-5 cm beneath the surface cover. However, not enough attention has been concentrated on the difference in these surface temperatures. This study aims at quantifying the distinction of surface temperatures by the comparisons and numerical simulations of observational field data collected in a discontinuous permafrost region on the northeastern Qinghai-Tibet Plateau (QTP). We compared the hourly, seasonal and yearly differences between T omega, IST, GST, and ground temperatures, as well as the freezing and thawing indices, the N-factors, and the surface and thermal offsets derived from these temperatures. The results showed that the peak hourly LST was reached earliest, closely followed by the hourly T-a. Mean annual LST (MALST) was moderately comparable to mean annual T-a (MAAT), and both were lower than mean annual GST (MAGST). Surface offsets (MAGST-MAAT) were all within 3.5 degrees C, which are somewhat consistent with other parts of the QTP but smaller than those in the Arctic and Subarctic regions with dense vegetation and thick, long-duration snow cover. Thermal offsets, the mean annual differences between the ground surface and the permafrost surface, were within -0.3 degrees C, and one site was even reversed, which may be relevant to equally thawed to frozen thermal conductivities of the soils. Even with identical T-a (comparable to MAAT of -3.27 and -3.17 degrees C), the freezing and thawing processes of the active layer were distinctly different, due to the complex influence of surface characteristics and soil, textures. Furthermore, we employed the Geophysical Institute Permafrost Lab (GIPL) model to numerically simulate the dynamics of ground temperature driven by T-a, LST, and GST, respectively. Simulated results demonstrated that GST was a reliable driving indicator for the thermal regime of frozen ground, even if no thermal effects of surface characteristics were taken into account. However, great biases of mean annual ground temperatures, being as large as 3 degrees C, were induced on the basis of simulations with LST and T-a when the thermal effect of surface characteristics was neglected. We conclude that quantitative calculation of the thermal effect of surface characteristics on GST is indispensable for the permafrost simulations based on the T-a datasets and the LST products-that derived from thermal infrared remote sensing.