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Warming temperatures and increasing disturbance by wildfire and extreme weather events is driving permafrost change across northern latitudes. The state of permafrost varies widely in space and time, depending on landscape, climate, hydrologic, and ecological factors. Despite its importance, few approaches commonly measure and monitor the changes in deep (>1 m) permafrost conditions with high spatial resolution. Here, we use electrical resistivity tomography surveys along two transects in interior Alaska previously disturbed by wildfire and more recently by warming temperatures and extreme precipitation. Long‐term point observations of permafrost depth, temperature, and water content inform geophysical measurements which, in turn, are used to extrapolate interpretations over larger areas and with high spatial fidelity. We contrast gradual loss of recently formed permafrost driven by warmer temperatures and increased snowfall, with rapid permafrost loss driven by changes in air temperature, snow depth, and extreme summer precipitation in 2014. Plain Language Summary: Permafrost, or ground that remains perennially frozen, is thawing across Arctic and sub‐Arctic regions, driven in part by climate warming, wildfire, and changes in the amount and timing of rain and snow. When permafrost thaws, previously frozen carbon can be released to the atmosphere as greenhouse gases, water flow and storage is altered, and community land use and access are impacted. Permafrost landscapes can be mapped over large areas from satellites or airborne remote sensing methods, but only at the surface with limited information obtained at depth. Measurements of deeper permafrost properties are often limited to point observations. We use geophysical measurements to indirectly map and monitor high spatial resolution changes in permafrost characteristics within the ground. Combined with point observations of soil temperature and moisture content, and thaw depths, geophysical measurements help to extend our ability to measure changing permafrost conditions over time. At two nearby transects in interior Alaska, we document the long‐term trajectory of permafrost thaw following wildfire. Our results show similar yet distinct responses in shallow permafrost recovery and more recent degradation, both gradual and rapid, caused by warming temperatures, increased snowfall, and extreme summer rainfall events. Key Points: Changes in the state of permafrost can be highly variable in both space and timeDisturbance or changes in climate and precipitation influence the long‐and short‐term trajectory of permafrost and seasonally frozen groundGeophysical measurements and monitoring complement direct permafrost observations by providing high resolution information at depth [ABSTRACT FROM AUTHOR]

Methane (CH4) emissions from climate-sensitive ecosystems within the northern permafrost region represent a potentially large but highly uncertain source, with current estimates spanning a factor of seven (11-75 Tg CH4 yr-1). Accelerating permafrost thaw threatens significant increases in pan-Arctic CH4 emissions, amplifying the permafrost carbon feedback. We used airborne imaging spectroscopy with meterscale spatial resolution and broad coverage to identify a previously undiscovered CH4 emission hotspot adjacent to a thermokarst lake in interior Alaska. Hotspot emissions were confined to <1% of the 10 ha lake study area. Ground-based chamber measurements confirmed average daily fluxes from the hotspot of 1,170 mg CH4 m-2 d-1, with extreme daily maxima up to 24,200 mg CH4 m-2 d-1. Ground-based geophysical measurements revealed thawed permafrost directly beneath the CH4 hotspot, extending to a depth of -15 m, indicating that the intense CH4 emissions likely originated from recently thawed permafrost. Hotspot emissions accounted for -40% of total diffusive CH4 emissions from the lake study site. Combining study site findings with hotspot statistics from our 70,000 km² airborne survey across Alaska and northwestern Canada, we estimate that pan-Arctic terrestrial thermokarst hotspots currently emit 1.1 (0.1--5.2) Tg CH4 yr-1, or roughly 4% of the annual pan-Arctic wetland budget from just 0.01% of the northern permafrost land area. Our results suggest that significant proportions of pan-Arctic CH4 emissions originate from disproportionately small areas of previously undetermined thermokarst emissions hotspots, and that pan-Arctic CH4 emissions may increase non-linearly as thermokarst processes increase under a warming climate. Plain Language Summary [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: Changes in the amount of water and ice below the surface, in both space and time, influence high latitude boreal ecosystems across many scales—from microorganisms living within the soils to the health and stability of aboveground plant, animal, and human communities. Warming temperatures and changes in precipitation have the potential to significantly weaken permanently frozen soils (permafrost), which can alter landscapes and the global carbon budget. However, the full scale of these impacts is not well understood. We used a unique combination of measurements to quantify spatial and temporal variation in unfrozen water content and examine possible linkages to methane concentrations in permafrost vulnerable to thaw. Our results show soils at temperatures below 0°C and adjacent to already‐thawed areas have relatively high levels of liquid water (5%–25%) and methane (up to 300,000 ppm), indicating these areas may be important for advancing thaw as well as for enhancing the ability of microbes to release carbon from the soils. Monitoring seasonal changes also revealed differences in the timing and nature of relationships between water and ice with carbon dioxide fluxes from the ground surface. These results provide a deeper understanding of how belowground water/ice influence biologic processes in high‐latitude ecosystems. Key Points: Permafrost near the freezing point contains 5%–25% liquid water and methane concentrations up to 300,000 ppmSupra‐permafrost talik zones at bog margins coincide with, and likely contribute to, elevated liquid water content in underlying permafrostInnovative geophysical and biogeochemical methods highlight how subsurface water/ice influence greenhouse gas concentrations and emissions [ABSTRACT FROM AUTHOR]

Growing water stress has led to emerging interest in protecting fresh and brackish groundwater as a potential supplement to water supplies and raised questions about factors that could affect the future quality of fresh and brackish aquifers. Limited well infrastructure, particularly in regions where elevated salinity has led to limited historical groundwater development, hinders traditional mapping of salinity distributions through groundwater sampling. This paper presents a quantitative salinity mapping approach of the upper 300 m using high‐resolution, regionally comprehensive resistivity models derived from Bayesian inversion of an airborne electromagnetic survey adjacent to the Lost Hills and Belridge oil fields in the southwestern San Joaquin Valley of California. Using local water quality observations as an interpretational foundation, a probabilistic approach yields maps of fresh, saline, and brackish groundwater while quantifying joint uncertainty inherited from the geophysical data and interpretational relations. Saline and fresh regions are mapped with relatively high confidence in many locations, while areas of lower confidence, particularly at depth, can be mapped as their most probable salinity category while reflecting the relative uncertainty in the interpretation. These maps identify a stratified salinity structure, where saline water commonly occurs in the surficial aquifer overlying fresher groundwater in the Tulare aquifer, separated by regional confining clay layers. Downgradient of unlined surface water diversions, recharge of imported surface water results in relatively fresh groundwater throughout the depth of investigation. Plain Language Summary: Salinity, a measure of salt concentration, can impact the potential use of groundwater. Salinity can be difficult to map using wells alone, especially where groundwater development has been limited in the past. Dissolved salts are excellent conductors of electricity, and resistivity measurements are commonly used to estimate salinity where wells are not available. Uncertainty in estimating salinity from resistivity data can be introduced into the interpretation by two sources: (1) how well we can estimate salinity from resistivity and (2) how accurately we can measure resistivity. We present a method for mapping salinity that accounts for both sources of uncertainty using regional‐scale, high‐resolution airborne geophysical data, leading to spatially comprehensive 3‐D maps of likely fresh (low salt) and saline (high salt) groundwater. The method is applied in the southwestern San Joaquin Valley of California adjacent to the Lost Hills and Belridge oil fields. Shallow groundwater is shown to have relatively high salinity in much of the study area, and a clay layer protects lower salinity water in the underlying Tulare aquifer. Leaking surface water canals have imported relatively fresh water into the area, resulting in fresher groundwater downgradient of the canals. Key Points: Fresh, brackish, and saline groundwater are mapped using airborne electromagnetic‐derived regional resistivity dataCategorical probability developed from Bayesian inversion and local wells reflect geophysical and interpretational uncertaintySurface water diversions and clay units strongly influence groundwater quality in the southwestern San Joaquin Valley [ABSTRACT FROM AUTHOR]

We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability. [ABSTRACT FROM AUTHOR]