High-Resolution Geomechanical Modeling Reveals Accelerating Infrastructure Risks from Permafrost Degradation in Northern Alaska

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Currently, the lack of community-scale, geomechanics-based mapping of Arctic infrastructure hazards hinders effective local infrastructure planning. Here, we develop a novel framework that integrates physics-constrained geotechnical models with a process-based ground thermal model to assess the 21st century changes in thaw settlement and bearing capacity of civil infrastructure foundations at a 30-m spatial resolution. We find that settlement is accelerating and bearing capacity is decreasing nonlinearly at both regional and local scales. By mid-century, less than 10% of the infrastructure in northern Alaska is projected to be at high risk; however, a tipping point emerges around the 2060s. Beyond the tipping point, most infrastructure will face high risk if mitigation measures are not implemented. Our results underscore the urgent need for proactive adaptation strategies to protect Arctic infrastructure from permafrost degradation-induced hazards. Earth and environmental sciences/Environmental social sciences/Climate-change adaptation Physical sciences/Engineering/Civil engineering Earth and environmental sciences/Climate sciences/Cryospheric science Earth and environmental sciences/Environmental social sciences/Climate-change impacts/Governance Earth and environmental sciences/Natural hazards Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction The Arctic is on the front line of global climate change and is warming about four times faster than the global mean 1 . Climate warming increases mean annual ground temperature in the Arctic and drives permafrost degradation 2 , 3 . Permafrost is defined as ground that remains below 0℃ for at least two consecutive years 4 , 5 . Permafrost degradation leads to ground ice melting, talik formation—defined as perennially unfrozen zones above or within the permafrost, thermokarst development, and associated thaw subsidence 6 , 7 . Degrading permafrost also alters the physical and mechanical properties of frozen soil and leads to reduced long-term strength 8 and lower bearing capacity 9 . Permafrost degradation has already caused irreversible damages to Arctic civil infrastructure and threatened Indigenous Arctic communities and the broader pan-Arctic economy 10 , 11 . Climate projections suggest that permafrost degradation will persist throughout the 21st century 12 , 13 . In Alaska and the pan-Arctic region, civil infrastructure geohazards driven by permafrost degradation are expected to intensify, posing challenges to the future adaptation of social systems and the built environment 14 – 16 . Thaw settlement and bearing capacity reduction are two dominant geohazards threatening civil infrastructure in permafrost regions 17 , 18 . When excess ground ice melts, thaw subsidence occurs due to the drainage of excess melt water. However, civil infrastructure imposes additional vertical stress on the ground; this leads to further settlement. Thaw settlement consists of volume reduction from both excess melt water drainage and stress-induced pore water drainage 19 . Although historically studied, current research primarily relies on “excess ice” models 20 to project thaw subsidence. The excess ice content is defined as the volumetric fraction of ice that exceeds the pore space of the thawed soil 21 . Consequently, the “excess ice” model underestimates thaw settlement for civil infrastructure, as it does not account for the consolidation of thawed soil due to pore water drainage. This underestimation may misinform regional planning and decision-making to support community adaptation efforts. In permafrost regions, bearing capacity of infrastructure foundation depends on the long-term strength of permafrost 22 . Long-term strength is defined as the maximum stress a soil can sustain without reaching a non-attenuating creep over the lifespan of an engineering structure 23 . As temperature increases, long-term strength decreases, leading to bearing capacity reduction and potential infrastructure damage. Long-term strength also varies with ground ice content. Experimental results indicate that long-term strength may be significantly lower than short-term strength 24 . Therefore, applying long-term strength to quantify bearing capacity aligns with engineering design principles and provides a more realistic projection of infrastructure stability. However, current geospatial assessments have not used long-term strength to quantify the bearing capacity of foundations in permafrost. To date, civil infrastructure geohazard assessments in permafrost studies have primarily been conducted at a relatively coarse spatial resolution, e.g., pan-Arctic 15 , 25 and state scales 26 , 27 . Due to ongoing and rapid climate change in the Arctic, there is an urgent need to assess civil infrastructure geohazards at the community scale to aid in local infrastructure planning and design 28 . In addition, there is a need to integrate environmental variables with geomechanics-based engineering design parameters to project bearing capacity and thaw settlement in support of community-scale assessments. We address this knowledge gap by producing the first 21st century community-scale (30-m spatial resolution) geohazard projections for civil infrastructure built on permafrost. We focus on the Arctic Coastal Plain and four coastal communities in northern Alaska. Supplementary Fig. 1 depicts the extent of the Arctic Coastal Plain and the location of the four coastal communities. Continuous permafrost underlies the region, consisting mainly of ice-rich silty sand 29 , 30 , 31 . See Section 1 of the Supplementary Information for a detailed description of the study region. In this study, we present an assessment framework that integrates geomechanical models with a process-based ground thermal model to evaluate the impact of permafrost degradation on civil infrastructure. Our model accounts for infrastructure loading effect on thaw settlement and calculates bearing capacity based on the creep failure mode of permafrost. This framework enables 30-m spatial resolution geohazard projections for civil infrastructure in the Arctic throughout the 21st century. We first quantify the magnitude and rate of changes in thaw settlement and bearing capacity at both regional (Arctic Coastal Plain) and local (four coastal communities) scales. We then assess the proportion of at-risk civil infrastructure in the Arctic Coastal Plain using the projected high-resolution geohazard data. Results Comparison between modeled and observed thaw subsidence rates We compare hindcast-modeled thaw subsidence rates ( \(\:{\dot{S}}_{e}\) ) with published data from two regions with existing measurements: near Point Barrow and Prudhoe Bay (Fig. 1 ). In-situ measurements near Point Barrow indicate thaw subsidence rates ranging from 0.4 cm to 1.0 cm per year between 2003 and 2015, with a total subsidence of 8 cm to 15 cm by 2015 32 . In Prudhoe Bay, InSAR observations recorded thaw subsidence rates ranging from 0.1 cm to 0.4 cm per year from 1992 to 2000 33 . Figure 1 a illustrates the spatial patterns of simulated thaw subsidence ( \(\:{S}_{e}\) ) between 2003 and 2015 and between 1992 and 2000 using RCP8.5. The study regions are marked by red boxes. Figure 1 b presents box plots of thaw subsidence in two-year intervals from 2005 to 2015 near Point Barrow. Figure 1 c shows a yearly time series plot of thaw subsidence from 1992 to 2000 near Prudhoe Bay. In Point Barrow, the simulated thaw subsidence rate increases from 0.6 to 1.5 cm per year under RCP8.5 and remains constant at 0.3 cm per year under RCP4.5. The simulated thaw subsidence by 2015 ranges from 10 cm to 13 cm under RCP8.5. In Prudhoe Bay, the rate increases from 0.2 to 0.4 cm per year under RCP8.5 and remains constant at 0.1 cm per year under RCP4.5. The simulations indicate an accelerating trend in thaw subsidence rates under the RCP8.5 climate forcing scenario. Hindcast simulations under RCP8.5 closely align with in-situ measurements 32 and InSAR observations 33 . Spatiotemporal variability of thaw settlement across Arctic Coastal Plain by the 2090s By the 2090s, higher projected thaw settlement is concentrated in the coastal regions from Wainwright to Point Lay and in lower-latitude areas under RCP8.5 (Fig. 2 a). This increased settlement is primarily driven by the higher compressibility of thawed soil, rapid thickening of the active layer and talik, and higher ground ice content in these regions. The mean thaw settlement ( \(\:\stackrel{-}{S}\) ) for the Arctic Coastal Plain reaches 1.1 m under RCP8.5 and 0.28 m under RCP4.5 when considering a vertical stress of 100 kPa due to infrastructure loading by the 2090s (Fig. 2 b). The stress level of 100 kPa is selected to represent the typical additional load imposed by low-rise residential buildings in cold regions. In geotechnical engineering, such structures typically impose vertical stress increments ranging from 50 kPa to 150 kPa. The use of 100 kPa provides a conservative yet realistic estimate of infrastructure-induced settlement. Moreover, applying a consistent stress value across the Arctic Coastal Plain allows for a comparable assessment across the study area. The scenario without vertical stress ( Δq = 0 kPa) represents conditions where no civil infrastructure load is applied (Fig. 2 c). Under this scenario, our projections indicate that the mean thaw subsidence reaches 0.42 m under RCP8.5 and 0.13 m under RCP4.5 by the 2090s. To further assess the validity of our model, we compare our projections with existing vertical ground surface displacement measurements in the Arctic Coastal Plain. Recent studies report total subsidence of 12 cm from 2001 to 2018 in the Eastern Coastal Plain near Deadhorse, Alaska, and 12 cm from 2003 to 2018 in the Western Coastal Plain near Utqiaġvik, Alaska 34 . These values correspond to a long-term subsidence rate of 0.07–0.08 m per decade in the past two decades 20 . Based on the observed rates, total thaw subsidence across the Arctic Coastal Plain over the next seven decades (from the 2020s to the 2090s) can be projected to be 0.49–0.56 m, which aligns with our projected mean thaw subsidence under RCP8.5. We statistically compare projected thaw settlement with and without infrastructure-induced vertical stress under RCP8.5 in Fig. 3 . Both scenarios exhibit a right-skewed distribution. By the 2090s, the mean thaw subsidence without infrastructure-induced loading is approximately 60% lower than that under a vertical stress of 100 kPa. The cumulative distribution function curve for the Δq = 0 kPa scenario consistently shifts to the left. This shift indicates that infrastructure loading contributes to increased thaw settlement. Our projections underscore the importance of incorporating infrastructure loading into thaw settlement assessments. Increased vertical stress imposed by civil infrastructure leads to compression of thawed sediments and additional thaw strain. This compression-induced thaw strain accelerates ground deformation as the permafrost table declines over time. As the rate of permafrost table decline increases 35 , the resulting additional deformation also increases over time. Neglecting these mechanical processes can significantly underestimate thaw settlement and potentially compromise infrastructure resilience planning in permafrost regions. Spatiotemporal variability of bearing capacity across Arctic Coastal Plain by the 2090s We project the spatial and temporal changes in ultimate bearing capacity ( \(\:{q}_{ult}\) ) using a semi-empirical equation derived from laboratory tests on ice-rich silty permafrost. The bearing capacity is calculated for a 5-m deep circular footing embedded in permafrost. This foundation represents a conventional pile foundation commonly used in northern Alaska 36 . We assume creep failure as the governing mode of failure. Ice-rich permafrost typically has high short-term strength but gradually weakens over time under a constant loading, a phenomenon known as creep. As such, long-term creep failure is the primary mechanism of foundation failure in permafrost regions 22 . By the 2090s, nearly the entire Arctic Coastal Plain exhibits an ultimate bearing capacity below 200 kPa under RCP8.5 (Fig. 4 a). A significant portion of the region near Point Lay and low-latitude areas experience a complete loss of bearing capacity due to mean annual ground temperatures rising above 0℃. In these areas, we assume that thawed sediments with high water content cannot support infrastructure loads and result in a total loss of bearing capacity. Under RCP4.5, ultimate bearing capacity exhibits greater spatial variation by the 2090s. The coastline from Utqiaġvik to Peard Bay and from Camden Bay to Kaktovik generally maintains higher bearing capacity of around 2000 kPa. In contrast, the coastlines near Point Lay and low-latitude regions exhibit lower bearing capacity, falling below 600 kPa. Low bearing capacity is primarily attributed to the low volume fraction of soil particles and high ground temperatures. As a result, the soil shows low creep resistance and low long-term strength in these areas. The mean ultimate bearing capacity ( \(\:{\stackrel{-}{q}}_{ult}\) ) of the Arctic Coastal Plain declines from 2050 kPa in the 2020s to 1470 kPa under RCP8.5 and 1588 kPa under RCP4.5 by the 2050s. By the 2090s, \(\:{\stackrel{-}{q}}_{ult}\) further decreases to 181 kPa under RCP8.5 and 1210 kPa under RCP4.5 (Fig. 4 b). Compared to the 2020s, \(\:{\stackrel{-}{q}}_{ult}\) decreases by 29% under RCP8.5 and 22% under RCP4.5 by the 2050s. By the 2090s, the reduction reaches 91% under RCP8.5 and 41% under RCP4.5 (Fig. 4 c). Previous projections for the North Slope Borough indicate that the mean bearing capacity of a pile foundation ranges from 1500 to 2500 kPa by 2040 26 . Our projections align with this range under both RCP8.5 and RCP4.5 by the 2040s. However, \(\:{\stackrel{-}{q}}_{ult}\) declines more rapidly over time under RCP8.5. Our projections indicate a severe long-term reduction in bearing capacity and potentially catastrophic damage to civil infrastructure in the absence of adequate design and mitigation measures. Accelerating thaw settlement in four coastal communities of northern Alaska Thaw settlement accelerates at both regional (see Fig. 2 ) and local (Fig. 5 ) scales. Utqiaġvik shows the lowest thaw settlement rate among the four communities, with mean thaw settlement reaching 0.13 m by the 2050s and 0.5 m by the 2090s (Fig. 5 a). In Wainwright, projected thaw settlement increases from 0.15 m in the 2050s to 1.1 m by the 2090s (Fig. 5 b). Point Lay exhibits the highest rate of thaw settlement, reaching 0.19 m by the 2050s and 2.7 m by the 2090s (Fig. 5 c). In Kaktovik, thaw settlement is projected to reach 0.3 m by the 2050s and 1.0 m by the 2090s (Fig. 5 d). The variation in projected thaw settlement among the four coastal communities is primarily driven by differences in the compressibility of thawed soil and the rate of permafrost table decline. In Utqiaġvik, permafrost typically exhibits a lower compressibility index and a slower decline in the permafrost table over time. In contrast, Point Lay experiences a rapid deepening of the permafrost table and a higher compressibility index (Supplementary Figs. 2 and 3), which leads to a thicker thawed layer for consolidation and a more pronounced volume decrease under vertical loading. By the 2030s, projected thaw settlement remains low across most areas of the four coastal communities and generally below 0.1 m compared to the 2020s (Fig. 6 ). However, localized zones of higher settlement—ranging from 0.7 m to 0.8 m—are observed along the Point Lay coastline and near the Kokolik River delta. By the 2050s, thaw settlement exhibits greater spatial heterogeneity. The coastlines of Utqiaġvik and Wainwright show increasing thaw settlement. In Point Lay, settlement intensifies along both the coastline and the Kokolik River delta. In Kaktovik, high settlement areas emerge in the northwestern and southeastern coastal regions of Barter Island. This increased thaw settlement by mid-century is primarily driven by the rapid thickening of the active layer near the coastlines and near the river deltas. By the 2090s, widespread talik development is projected across all four coastal communities. Talik development contributes significantly to thaw settlement. Extensive talik formation is expected in the northeastern part of Utqiaġvik, where thermokarst lakes are present. Talik also develops extensively in northeastern Wainwright, along the Kokolik River delta in Point Lay, and in the northwestern and southeastern coastal areas of Barter Island near Kaktovik. Talik formation in these regions is attributed to the heat storage effect of surface water 37 and the presence of saline ground material 38 . Nonlinear bearing capacity loss in four coastal communities of northern Alaska The bearing capacity decreases nonlinearly over time at both regional (see Fig. 4 ) and local (Fig. 7 ) scales. In Utqiaġvik, the rate of decrease in mean bearing capacity remains relatively low in the first half of the century. By the 2050s, \(\:{\stackrel{-}{q}}_{ult}\) declines from 1750 kPa to 1370 kPa, representing a 22% reduction (Fig. 7 a). However, the rate of decline accelerates over time. By the 2090s, \(\:{\stackrel{-}{q}}_{ult}\) is projected to reach 157 kPa with a 91% reduction compared to the 2020s. In Wainwright and Point Lay, \(\:{\stackrel{-}{q}}_{ult}\) declines more rapidly in the first half of the century and reaches critically low values by the 2090s. Specifically, \(\:{\stackrel{-}{q}}_{ult}\) in Wainwright decreases from 1780 kPa to 1140 kPa by the 2050s —a 36% reduction. By the 2090s, \(\:{\stackrel{-}{q}}_{ult}\) further declines by 95% compared to the 2020s (Fig. 7 b). Among the four communities, Point Lay exhibits the most severe decline in \(\:{\stackrel{-}{q}}_{ult}\) . \(\:{\stackrel{-}{q}}_{ult}\) decreases from 1860 kPa to 600 kPa (68% reduction) by the 2050s and ultimately reaches 0 kPa by the 2090s (Fig. 7 c). Kaktovik experiences a relatively less severe decline in \(\:{\stackrel{-}{q}}_{ult}\) (Fig. 7 d). The projected \(\:{\stackrel{-}{q}}_{ult}\) decreases from 2810 kPa in the 2020s to 2190 kPa by the 2050s (22% reduction) and 320 kPa by the 2090s (89% reduction). Changes in mean annual ground temperature are the primary factor influencing the evolution of ultimate bearing capacity over time across the four coastal communities. Permafrost near Utqiaġvik generally exhibits lower ground temperatures and a slower rate of increase under the RCP8.5 climate forcing. In contrast, the coastline spanning from Point Lay to Wainwright experiences higher ground temperatures and a more rapid increase over time. Elevated temperatures reduce the creep resistance of permafrost, leading to lower long-term strength and ultimately a significant decline in bearing capacity. The projected ultimate bearing capacity exhibits high spatial heterogeneity across the four coastal communities (Fig. 8 ). In Utqiaġvik, higher bearing capacity is concentrated near the coastline. A similar spatial pattern is observed in Wainwright, where bearing capacity remains higher near the coastline and lower in inland areas by the 2050s. Point Lay exhibits relatively low bearing capacity across the entire community in both the 2030s and the 2050s compared with the other three communities. In Kaktovik, lower bearing capacity is concentrated in the northwestern and southeastern regions of Barter Island by the 2050s. By the 2090s, bearing capacity across the four communities decreases to low levels showing reduced spatial variability. At a given time, the spatial distribution of bearing capacity is primarily governed by variations in the volumetric fraction of soil particles ( θ s ). A higher θ s is directly related to a higher bulk density for the same soil type. Experimental tests suggest that denser, ice-rich silty permafrost exhibits higher creep resistance and long-term strength due to the densification effect on deformation 39 . Consequently, when other soil conditions remain unchanged, a higher θ s tends to result in higher bearing capacity. In Utqiaġvik and Wainwright, regions with higher θ s —primarily near the coastline—exhibit correspondingly higher bearing capacity. Similarly, higher bearing capacity is concentrated in the northeastern region of Barter Island in Kaktovik due to the relatively high θ s . Although θ s in Point Lay is also relatively high, ranging from 0.35 to 0.45, a large portion of the region experiences a rapid rise in mean annual ground temperatures above 0°C by the 2090s. As a result, Point Lay undergoes a drastic loss of bearing capacity due to permafrost degradation. 21st century infrastructure risks under permafrost degradation We quantify 21st century infrastructure risks ( I risk ) on the Alaska Arctic Coastal Plain. See Methods for a detailed description of infrastructure risk assessment. Infrastructure risk remains low by the 2050s (Fig. 9 ). Our projections indicate that the percentage of buildings at risk is 7%, 4%, and 0% for design safety factors of 1.6, 2.0, and 3.0, respectively, under RCP8.5 (Fig. 9 a). By the 2050s, 2%-3% of roads and 1%-3% of pipelines are also at risk. However, infrastructure risk significantly increases after a tipping point in the 2060s. By the 2070s, 68% of buildings are projected to experience at least a 50% reduction in bearing capacity. Forty-five percent of roads and 52% of pipelines are projected to exceed the 0.2 m settlement threshold under moderate stress conditions. By the 2090s, our projections indicate that 80%-83% of buildings are at risk due to substantial bearing capacity reduction. 58%-60% of roads and 87%-90% of pipelines are projected to be exposed to high thaw settlement. Under RCP4.5, infrastructure risks are significantly lower (Fig. 9 b). By the 2090s, projections indicate that 6%-36% of buildings and 2%-3% of roads and pipelines are at risk under RCP4.5. Shaded areas in Fig. 9 represent uncertainties associated with variations in factors of safety and vertical stress. The tipping point around the 2060s results from the long-term effects of climate change on permafrost. By the 2060s, large areas exhibit increased thaw settlement and a decline in bearing capacity beyond critical thresholds. Geohazards exceeding these thresholds place most infrastructure on the Arctic Coastal Plain at high risk and mark the tipping point. Our projections underscore the urgency of adaptation-based policies and mitigation measures, along with the need to reduce global emissions to prevent unprecedented infrastructure damage. However, our projections do not account for uncertainties related to future human activities. The impact of human activities could either exacerbate infrastructure risks in the absence of adaptation strategies or mitigate them through proactive planning and engineering solutions. Discussion To enable early warning systems and anticipatory actions for mitigating Arctic infrastructure risks, state and local governments and Indigenous communities require accurate and high-spatial-resolution tools and projections to visualize infrastructure geohazards. Projecting the spatiotemporal rate and magnitude of these geohazards is essential to support future adaptation efforts and ensure the resilience of both social systems and the built environment to the unprecedented environmental changes in the Arctic. This study presents a framework capable of generating high-resolution, time-series hazard maps through the end of the 21st century. The outcomes of this study can assist planners and policymakers in identifying high-risk areas, implementing mitigation measures, and strategically planning future infrastructure at the community scale. When compared with existing literature, our work presents several key innovations that distinguish this study from earlier hazard assessments. First, our framework is geomechanics-based, in contrast to previous studies that primarily relied on indices or statistical models alone. By integrating geomechanical models with a process-based ground thermal model, the approach captures the mechanical behavior of permafrost under varying stress and thermal conditions more accurately. Second, our thaw settlement projections account for settlement induced by increased vertical stress. The model therefore considers how additional loads from civil infrastructure contribute to increased surface deformation. This infrastructure loading effect is often overlooked in previous studies, where thaw settlement is typically estimated based solely on excess melt water drainage. Third, many prior hazard mapping approaches focused on short-term permafrost stability, without adequately accounting for its progressive weakening. However, permafrost used as a foundation material often experiences creep failure when accumulated strain exceeds the failure strain within a structure’s service life. We address this gap by estimating bearing capacity based on the long-term strength of ice-rich permafrost. Long-term strength is a critical factor in cold region foundation design and is related to creep resistance of the frozen soil. Finally, our framework presents high-resolution 30-m hazard maps, substantially finer than the coarser-scale outputs (e.g., 1 km or 10 km grids) in previous studies. The high spatial resolution is essential for identifying localized risks related to infrastructure damage, socio-economic impact, and landscape evolution. With these four innovations, our study provides the first precise, geomechanics-based framework for understanding how permafrost degradation and associated hazards evolve at both local and regional scales. Despite the strengths of our approach, the infrastructure hazard assessment is subject to uncertainties related to data, process representation, human influences, climate forcing, and model validation (see Section 4 of the Supplementary Information). First, the modeling of permafrost dynamics is constrained by limited field-based ground measurements. Second, the time-dependent consolidation behavior of thawing soils and the time required to reach ultimate settlement 39 are not considered in the current framework. Third, real-world engineering practices include a wide range of foundation types and dimensions. Finally, in terms of subsurface features, the current framework does not model the development of cryopegs 41 or account for the role of cryopegs in permafrost stability. Future research is recommended to reduce uncertainty and further improve hazard mapping by addressing limitations of the current framework. In conclusion, our findings reveal that thaw settlement is accelerating and bearing capacity is decreasing nonlinearly at both regional (Arctic Coastal Plain) and local (Utqiaġvik, Wainwright, Point Lay, and Kaktovik) scales. In the four coastal communities, thaw settlement is projected to reach 0.15–0.3 m by the 2050s and 0.5–2.7 m by the 2090s under RCP8.5. Omitting the effect of infrastructure-induced stress leads to an underestimation of thaw settlement. Rising ground temperatures weaken permafrost, resulting in a 22–68% reduction in bearing capacity by the 2050s and 88–100% by the 2090s in the four coastal communities. Permafrost degradation places 80% of buildings, 60% of roads, and 90% of pipelines at high risk by the 2090s across the Arctic Coastal Plain. While the projected percentage of infrastructure at high risk remains below 10% by the mid-century, a clear tipping point of infrastructure failure emerges in the 2060s. Beyond the tipping point, most infrastructure will face high risk if mitigation measures are not implemented and greenhouse gas emissions continue unabated. Our findings underscore the urgent need for proactive adaptation strategies to support coastal communities. Moving forward, further research focused on high-resolution hazard mapping at the community scale will be critical. Future efforts should also integrate Indigenous knowledge to co-produce evidence-based decision-making frameworks for Arctic and sub-Arctic regions. Methods Data We obtained soil information (i.e., soil bulk density, clay content) from SoilGrids 42 . SoilGrids provids a global estimation of soil properties at a spatial resolution of 250 m. All geospatial data are resampled to 30 m in our analysis to match the outputs from the process-based ground thermal model. The estimated soil properties were provided for seven standard depths from the ground surface to 200 cm. The soil properties were derived using machine learning algorithms trained on global soil profiles. We used the depth-weighted average to obtain soil properties at each location. The soil bulk density and clay content are shown in Supplementary Figs. 2a and 2b. We used the ground ice map of northern Alaska 43 in our assessment. The ground ice map illustrates the distribution of excess ground ice volume within the upper five meters of permafrost. Supplementary Fig. 2c shows the ground ice distribution across the Arctic Coastal Plain. The permafrost temperature dynamics were simulated using the GIPL-2.0 model 38 . GIPL-2.0 is a process-based model that solves the 1-D nonlinear heat conduction equation with phase change to simulate permafrost conditions, including ground temperature, active layer thickness, and talik thickness. The governing equation is presented in Eq. (1) 44 . $$\:\left({C}_{v}+L\frac{\partial\:{\theta\:}_{w}\left(T,z\right)}{\partial\:T}\right)\frac{\partial\:T}{\partial\:t}=\frac{\partial\:}{\partial\:z}\left(\lambda\:\frac{\partial\:T\left(z,t\right)}{\partial\:z}\right)$$ 1 where z is the depth from the soil or snow surface, T is the ground temperature, C v represents the volumetric heat capacity, λ is the thermal conductivity, L is the volumetric latent heat of fusion, and θ w represents the volumetric water content. The simulations utilized downscaled air-temperature datasets 45 , 46 to drive permafrost dynamics at a 30-m spatial resolution under the RCP4.5 and RCP8.5 climate forcing. Ground thermal properties and volumetric water content were parameterized and upscaled based on high-resolution ecosystem type classifications and borehole data. Supplementary Figs. 2d, 2e, and 2f illustrate the projected permafrost conditions by the 2050s. Suppelmentary Figs. 2 g, 2 h, and 2 i depict the permafrost projections in the 2090s. We incorporate the existing simulation data into our geohazard assessment to evaluate the impacts of permafrost degradation on civil infrastructure. Assessment of Thaw Settlement When permafrost warms and thaws, excess melt water first drains out without the compression of the soil skeleton 47 . Thaw subsidence related to excess ice melt can be expressed as 18 , 36 , 48 : $$\:{S}_{e}={\varDelta\:Z}_{ALT+TT}{\theta\:}_{excess,\:\:ice}$$ 2 where S e is the subsidence related to excess ice melt, ΔZ represents changes in the permafrost table due to active layer thickening or talik development, ALT denotes active layer thickness, TT is talik thickness, and θ excess,ice is the volumetric content of excess ice. Supplementary Table 1 contains the notations of parameters used in the geomechanical modeling. Calculating thaw subsidence solely from excess ice content is valid only when the compression of the soil skeleton is negligible. However, vertical stress increases from infrastructure loading cause additional volume reduction due to pore water drainage in the thawed sediment. For ice-rich permafrost, whether coarse-grained or fine-grained, the volume decrease during thawing consists of three main components: phase change, drainage of excess melt water, and compression of thawed sediments under the applied stress 47 , 49 . After the excess melt water drains out, the void ratio of the thawed soil follows a semilogarithmic linear relationship with the stress carried by the soil skeleton 50 . Therefore, the volume change in thawed permafrost due to pore water drainage can be expressed as follows: $$\:{S}_{c}=\frac{{e}_{th}-e}{1+{e}_{th}}\varDelta\:{Z}_{ALT+TT}=\frac{\varDelta\:{Z}_{ALT+TT}}{1+{e}_{th}}{C}_{c}^{*}\text{log}\frac{{\sigma\:}_{0}^{{\prime\:}}+\varDelta\:q}{{\sigma\:}_{0}^{{\prime\:}}}$$ 3 where S c is the settlement related to compression of the soil skeleton, e th represents the thawed void ratio after excess melt water drains out, \(\:{C}_{c}^{*}\) is the coefficient of compressibility of the thawed soil (i.e., the slope of the semilogarithmic linear curve between void ratio and stress carried by soil skeleton), \(\:{\sigma\:}_{0}^{{\prime\:}}\) is the residual stress, which is defined as the initial effective stress within the soil skeleton when the soil thaws under undrained conditions 51 , Δq is the vertical stress increment caused by infrastructure loading, and e is the thawed void ratio at \(\:{\sigma\:}_{0}^{{\prime\:}}\) + Δq . The settlement induced by phase change from frozen state to thawed state is expressed as: $$\:{S}_{p}=\frac{{e}_{f}-{e}_{i}^{*}}{1+{e}_{f}}{\varDelta\:Z}_{ALT+TT}$$ 4 where S p is the settlement related to phase change, e f is the frozen void ratio, and \(\:{e}_{i}^{*}\) is the initial thawed void ratio. We use bulk density and specific gravity (based on soil types) to calculate e f for saturated permafrost in the Arctic Coastal Plain. Since the void ratio decreases from e f to \(\:{e}_{i}^{*}\) solely due to phase change, the relationship between e f and \(\:{e}_{i}^{*}\) is expressed as: $$\:{e}_{i}^{*}=\frac{{e}_{f}}{1.09}$$ 5 The total thaw settlement S is therefore written as: $$\:S={S}_{p}+{S}_{e}+{S}_{c}$$ 6 We use experimentally determined relationships to calculate \(\:{C}_{c}^{*}\) and e th . \(\:{\sigma\:}_{0}^{{\prime\:}}\) is assumed to be 0.1 kPa for ice-rich permafrost 52 . The expression for \(\:{C}_{c}^{*}\) is adopted from an empirical equation developed using 108 tests on ice-rich permafrost 47 : $$\:{C}_{c}^{*}=\left(0.0051clay\%-0.18\right)\text{log}{e}_{i}^{*}+(0.0015clay\%+0.096)$$ 7 where clay% represents gravimetric clay content. We calculate e th based on empirical relationships between e th and e f developed from thaw settlement tests ice-rich permafrost 52 : $$\:{e}_{th}=1.82\text{log}{e}_{f}+0.95$$ 8 Supplementary Figs. 3a, 3c, and 3e show the spatial distribution of e f , e th , and \(\:{C}_{c}^{*}\) , respectively. Higher values of e f and e th are concentrated in the higher-latitude tundra. However, permafrost along the coastline from Utqiaġvik to Wainwright exhibits lower values of e f and e th . A similar pattern is observed for \(\:{C}_{c}^{*}\) , with lower values prevalent near the coastline from Utqiaġvik to Wainwright and around Elson Lagoon along the Beaufort Sea. Supplementary Figs. 3b, 3d, and 3f present the histograms of e f , e th , and \(\:{C}_{c}^{*}\) , respectively. Each parameter follows a normal distribution. The mean and median values are 2.15 and 2.08 for e f , 1.54 and 1.53 for e th , and 0.24 and 0.25 for \(\:{C}_{c}^{*}\) . These values fall within typical ranges observed for ice-rich permafrost. Assessment of Bearing Capacity The long-term strength ( σ lt ) for ice-rich permafrost is calculated using Eq. (9) 22 . $$\:{\sigma\:}_{lt}={\left(\frac{{ϵ}_{f}}{{t}_{f}A}\right)}^{1/n}\:$$ 9 where ε f is the failure strain. For ice-rich permafrost, ε f is assumed to be 0.1 22 . t f represents the service life of civil infrastructure. We set t f to 50 years. A and n are creep parameters in Glen’s flow law 53 . We use semi-empirical equations to determine A and n based on volumetric soil particle fraction ( θ s ) and ground temperature ( T ) at 5-m depth, which represents the depth of conventional pile foundations. For saturated permafrost, θ s is derived from bulk density and specific gravity. The semi-empirical equations were developed through unconfined creep tests of 29 ice-rich silty permafrost samples from northern Alaska 8 . Eq. ( 10 ) presents the expression for the creep parameters: $$\:A=\text{exp}\left(-14.1-154.1{\theta\:}_{s}+\frac{186.9}{1+\left|T\right|}{\theta\:}_{s}\right)\:n=1.4+20.1{\theta\:}_{s}-\frac{19.6}{1+\left|T\right|}{\theta\:}_{s}$$ 10 Supplementary Fig. 4 illustrates the projected creep parameters and long-term strength of permafrost for the 2020s, 2050s, and 2090s under RCP8.5 climate forcing. By the 2090s, the mean annual ground temperature exceeds 0℃ in some areas, leading to permafrost loss and complete bearing capacity reduction. Grid cells where the mean annual ground temperature exceeds 0℃ are excluded from the analysis. In the 2020s, σ lt is relatively lower in higher-latitude coastal regions due to lower soil particle fractions. In contrast, permafrost along the coastline from Utqiaġvik to Wainwright exhibits higher σ lt values. However, as ground temperatures rise rapidly in lower-latitude regions by the 2050s and 2090s, spatial variations in σ lt become less pronounced. Supplementary Fig. 5 presents the histograms of creep parameters and long-term strength for the 2020s, 2050s, and 2090s under RCP8.5. Each parameter follows a normal distribution. An exception is observed in the 2090s, where σ lt exhibits a right-skewed distribution. The mean and median values of logA increase from − 24.0 in the 2020s to -8.4 and − 8.5 in the 2090s, respectively. The mean and median values for n decrease from 7.0 in the 2020s to 3.2 and 3.1 in the 2090s. These values are consistent with previously documented creep parameters for ice-rich permafrost 54 . The mean σ lt declines sharply from 305.6 kPa in the 2020s to 11.5 kPa in the 2090s. This sharp decrease indicates a substantial loss of permafrost strength due to climate change. The ultimate bearing capacity ( q ult ) is determined using σ lt based on Eq. (11) 55 : $$\:{q}_{ult}={p}_{0}{N}_{q}+c{N}_{c}\:$$ 11 where ρ 0 is the ground overburden pressure at the foundation level. We calculate ρ 0 using specific gravity and foundation depth. c represents temperature-dependent cohesion, while N q and N c are the bearing capacity factors. For ice-rich permafrost with friction angle ( \(\:\varphi\:\) ) of zero, N q is equal to 1 and c is equal to half of σ lt . N c for a circular footing is defined by Eq. (12) 55 . $$\:{N}_{c}=1+\frac{4}{3}\left(n+\text{ln}\frac{2}{3{\epsilon\:}_{f}}\right)\:$$ 12 For a strip footing, N c is defined by Eq. (13) 56 . $$\:{N}_{c}=\frac{2}{\sqrt{3}}\left[1+n-\text{ln}{\epsilon\:}_{f}\sqrt{3}\right]$$ 13 Assessment of Infrastructure Risks The high spatial resolution (30-m), geomechanics-based projections enable a community-scale assessment of geohazards caused by permafrost degradation. Raster cell values within each community polygon are extracted and analyzed using time-series plots to assess the rate and magnitude of thaw settlement (Fig. 5 ) and ultimate bearing capacity changes (Fig. 7 ) in each community. We assess infrastructure risks based on projected thaw settlement and bearing capacity reduction. Infrastructure data are obtained from the North Slope Science Initiative. Supplementary Fig. 6 outlines the workflow in ArcGIS Pro 57 . The analysis begins by extracting raster maps of bearing capacity and thaw settlement based on predefined threshold values. The threshold values are denoted as θ bc * and S * for bearing capacity reduction and thaw settlement, respectively. The extracted hazard maps are then converted into polygon features and intersected with infrastructure locations to identify at-risk infrastructure. Next, we calculate the area or length of at-risk infrastructure. The fraction of at-risk infrastructure is calculated as the ratio of at-risk area or length to the total infrastructure extent. To represent road-induced loading conditions, we select vertical stress values of 10, 30, and 50 kPa. These stress values capture the range from conservative far-field stress to localized peak stress typically observed under roadways. For pipelines, vertical stress values of 5, 15, and 25 kPa are used to reflect common pipeline-induced loading conditions. For buildings, infrastructure at high risk is determined based on the loss of bearing capacity exceeding a threshold value ( \(\:{\theta\:}_{bc}^{*}\) ) of 35%, 50%, and 65%. The selected \(\:{\theta\:}_{bc}^{*}\) values correspond to design safety factors of 1.6, 2.0, and 3.0, respectively, assuming infrastructure damage occurs when the bearing capacity falls below a safety factor of 1. Design safety factors are the factors used in foundation designs; a higher factor represents a more conservative design applied in construction. Declarations Competing interests The authors declare no competing interests. Author contributions Z.W. and M.X. designed the study. D.N. developed the permafrost ground thermal model. Z.W. developed the geomechanics-based method, performed the analysis and wrote the manuscript. Acknowledgments This work was supported by the U.S. National Science Foundation (NSF) Award RISE-1927718. References Rantanen M et al (2022) The Arctic has warmed nearly four times faster than the globe since 1979. Commun Earth Environ 3:168 Biskaborn BK et al (2019) Permafrost is warming at a global scale. 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ArcGIS Pro (Version 3.X) [Computer software] (2024) ; https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview Additional Declarations There is NO Competing Interest. Supplementary Files Supinfrastructurehazardassessment.docx Supplementary Information Cite Share Download PDF Status: Published Journal Publication published 23 Jan, 2026 Read the published version in Communications Earth & Environment → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7055543","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":482494888,"identity":"e9dfa9b5-3f95-4dc0-9dc7-9c92c228672b","order_by":0,"name":"Ziyi 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06:24:36","extension":"xml","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":133549,"visible":true,"origin":"","legend":"","description":"","filename":"NCOMMS25520480structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/c4da723615cb606f1332be1e.xml"},{"id":94822485,"identity":"a8a34e94-dc00-467c-80ec-b89a874968e5","added_by":"auto","created_at":"2025-10-31 06:24:36","extension":"html","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":148426,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/965452e6484180c828d9b0f5.html"},{"id":94826440,"identity":"bbd84b8c-f7e6-4c78-88e4-92487d5a4889","added_by":"auto","created_at":"2025-10-31 06:51:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":877856,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial patterns and temporal trends of hindcast-modeled thaw subsidence. a, Maps of simulated thaw subsidence under RCP8.5 for 2003-2015 (top) and 1992-2000 (bottom). Inserted maps highlight the study regions near Pt. Barrow and Prudhoe Bay used for model comparison. Subsidence is estimated based on permafrost table changes and excess ice content (equation (2)). b, c, Time series of thaw subsidence in the two study regions under RCP8.5 and RCP4.5. Box plots show the median (center line), mean (square), interquartile range (25th to 75th percentile, box), and whiskers extending to 1.5 times the interquartile range. Polynomial regression is applied to fit the mean values. The model simulates thaw subsidence under conditions where additional vertical stress Δq = 0 kPa, representing undisturbed ground without civil infrastructure to match the conditions under which in-situ measurements and InSAR observations were taken.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/129a6653cde9a056128a2b96.png"},{"id":94822466,"identity":"9eee578c-0a15-45f4-be99-424db89e7954","added_by":"auto","created_at":"2025-10-31 06:24:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":735910,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpatial patterns and temporal trends of thaw settlement on the Arctic Coastal Plain by the 2090s.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, Projected thaw settlement by the 2090s under RCP8.5 (\u003cem\u003etop\u003c/em\u003e) and RCP4.5 (\u003cem\u003ebottom\u003c/em\u003e). An infrastructure-induced vertical stress increase of 100 kPa is assumed. Thaw settlement is calculated relative to the 2020s. \u003cstrong\u003eb\u003c/strong\u003e, Decadal changes in mean thaw settlement under applied vertical stress of 100 kPa for RCP8.5 and RCP4.5. \u003cstrong\u003ec\u003c/strong\u003e, Decadal changes in mean thaw subsidence under undisturbed conditions for RCP8.5 and RCP4.5. Shaded regions indicate ±1\u003cem\u003eσ\u003c/em\u003e spatial variability in thaw settlement across the study area, where \u003cem\u003eσ\u003c/em\u003e represents standard deviation.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/b22e11a5bb8d8705ae62cd81.png"},{"id":94822467,"identity":"11c84c41-e20c-4f9b-b42e-47f7279062e0","added_by":"auto","created_at":"2025-10-31 06:24:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":51377,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of thaw settlement with and without infrastructure loading.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, Histogram of thaw settlement with and without a 100 kPa vertical stress by the 2090s relative to the 2020s under RCP8.5. \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003ecells\u003c/em\u003e\u003c/sub\u003e represent the number of grid cells across the Arctic Coastal Plain. \u003cstrong\u003eb\u003c/strong\u003e, Cumulative distribution of thaw settlement with and without a 100 kPa vertical stress by the 2090s relative to the 2020s under RCP8.5.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/45b54930099fb59b05fbb4f6.png"},{"id":94822469,"identity":"28eee50b-185a-4da4-b7e0-9da0a63797a7","added_by":"auto","created_at":"2025-10-31 06:24:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":749783,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpatial patterns and temporal trends of bearing capacity on the Arctic Coastal Plain by the 2090s.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, Projected bearing capacity by the 2090s under RCP8.5 (\u003cem\u003etop\u003c/em\u003e) and RCP4.5 (\u003cem\u003ebottom\u003c/em\u003e). \u003cstrong\u003eb\u003c/strong\u003e, Decadal changes in mean bearing capacity for RCP8.5 and RCP4.5. \u003cstrong\u003ec\u003c/strong\u003e, Decadal changes in mean bearing capacity reduction (%) for RCP8.5 and RCP4.5. Bearing capacity reduction is calculated relative to the 2020s. Shaded regions indicate ±1\u003cem\u003eσ\u003c/em\u003espatial variability in bearing capacity across the study area.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/473c9ab717b18a9a3ca15c70.png"},{"id":94822470,"identity":"84dd7421-10e8-408d-9d7e-b2c2ec3544cd","added_by":"auto","created_at":"2025-10-31 06:24:35","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":129782,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChanges in thaw settlement in four coastal communities in northern Alaska by the 2090s.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, Projected thaw settlement in Utqiaġvik. \u003cstrong\u003eb\u003c/strong\u003e, Projected thaw settlement in Wainwright. \u003cstrong\u003ec\u003c/strong\u003e, Projected thaw settlement in Point Lay. \u003cstrong\u003ed\u003c/strong\u003e, Projected thaw settlement in Kaktovik. Thaw settlement is calculated relative to the 2020s under RCP8.5 climate forcing. Box plots show the median (center line), interquartile range (25\u003csup\u003eth\u003c/sup\u003e to 75\u003csup\u003eth\u003c/sup\u003e percentile, box), and whiskers extending to 1.5 times the interquartile range. A second-order polynomial regression is applied to fit the trend. Time series of \u003cimg width=\"9\" height=\"27\" src=\"data:image/png;base64,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\"/\u003e\u0026nbsp;are well described by quadratic polynomial fits with \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e values ranging from 0.96 to 0.99. The shaded region represents the 95% confidence interval of the fitted curve for the seven \u003cem\u003e\u003cstrong\u003eS̄\u003c/strong\u003e\u003c/em\u003e\u0026nbsp;projections. Thaw settlement in four coastal communities was projected using a vertical stress increase of 100 kPa to represent typical civil infrastructure loading conditions. See Fig. 3 for comparison of thaw settlement with and without infrastructure loading.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/4558018d3e630ff3135f47dc.png"},{"id":94826555,"identity":"65b79b71-e5eb-4d22-8346-8e5f3297aa76","added_by":"auto","created_at":"2025-10-31 06:52:10","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":746516,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpatial patterns of projected 21\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003est\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e century thaw settlement in four coastal communities in northern Alaska.\u003c/strong\u003e Projected thaw settlement for the next decade (2030s), mid-century (2050s), and end-of-century (2090s) in: Utqiaġvik (first row), Wainwright (second row), Point Lay (third row), and Kaktovik (fourth row). Thaw settlement is calculated relative to the 2020s under RCP8.5 climate forcing.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/76499b6fe5fa35116b29b4a2.png"},{"id":94826533,"identity":"e0d85882-998e-4fb7-bd13-fd69483bb0a7","added_by":"auto","created_at":"2025-10-31 06:52:03","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":107113,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChanges in bearing capacity in four coastal communities in northern Alaska by the 2090s.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, Projected bearing capacity in Utqiaġvik. \u003cstrong\u003eb\u003c/strong\u003e, Projected bearing capacity in Wainwright. \u003cstrong\u003ec\u003c/strong\u003e, Projected bearing capacity in Point Lay. \u003cstrong\u003ed\u003c/strong\u003e, Projected bearing capacity in Kaktovik. Bearing capacity is calculated under RCP8.5 climate forcing. Box plots show the median (center line), interquartile range (25\u003csup\u003eth\u003c/sup\u003e to 75\u003csup\u003eth\u003c/sup\u003e percentile, box), and whiskers extending to 1.5 times the interquartile range. A second-order polynomial regression is applied to fit the trend. Time series of q̅ult\u003cimg width=\"25\" height=\"27\" src=\"data:image/png;base64,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\"/\u003e\u0026nbsp;are well represented by quadratic polynomial fits with \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e values ranging from 0.97 to 0.99. The shaded region represents the 95% confidence interval of the fitted curve for the seven \u003cimg width=\"25\" height=\"27\" src=\"data:image/png;base64,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\"/\u003eq̅ult\u0026nbsp;projections. The ultimate bearing capacity in the four coastal communities was projected using semi-empirical equations (equations (9) to (13)). A 5-m deep pile foundation is selected to estimate bearing capacity at the community scale. See Supplementary Fig. 7 for comparison of bearing capacity estimates for deep circular footings and shallow strip footings.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/7bccd1fec95d881da96927f3.png"},{"id":94826223,"identity":"6afa84db-bc0b-4b19-8abb-06ec12b7bcdc","added_by":"auto","created_at":"2025-10-31 06:51:16","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":755554,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpatial patterns of projected 21\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003est\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e century bearing capacity in four coastal communities in northern Alaska.\u003c/strong\u003e Projected bearing capacity for the next decade (2030s), mid-century (2050s), and end-of-century (2090s) in: Utqiaġvik (first row), Wainwright (second row), Point Lay (third row), and Kaktovik (fourth row). Bearing capacity is calculated under RCP8.5 climate forcing.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/5579b938aa816b966a309e13.png"},{"id":94822476,"identity":"1c953046-20d8-47a6-904c-197b213f7b23","added_by":"auto","created_at":"2025-10-31 06:24:35","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":80187,"visible":true,"origin":"","legend":"\u003cp\u003eCivil infrastructure at risk due to permafrost degradation on Alaska’s Arctic Coastal Plain over the 21st century. a, Infrastructure risk assessed under RCP8.5. b, Infrastructure risk assessed under RCP4.5. For buildings, infrastructure at high risk is determined based on the loss of bearing capacity. Light blue envelopes represent uncertainty due to the design safety factor of buildings, where the upper, middle, and lower ranges correspond to a 35%, 50%, and 65% reduction in bearing capacity compared to the 2020s. The threshold bearing capacity reduction (θ*\u003csub\u003ebc\u003c/sub\u003e) values correspond to design safety factors of 1.6, 2.0, and 3.0, respectively, assuming infrastructure damage occurs when the bearing capacity falls below a safety factor of 1. For linear infrastructure such as roads and pipelines, settlement is the primary factor contributing to damage and maintenance challenges9. Light yellow and red envelopes represent uncertainty due to infrastructure-induced vertical stress on the ground. The threshold settlement (S*) used to define high-risk linear infrastructure is set at 0.2 m40. For roads, vertical stress values of 10, 30, and 50 kPa are considered. For pipelines, vertical stress values of 5, 15, and 25 kPa are considered.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/e627c931e21c1e90bdbfe8b6.png"},{"id":104098307,"identity":"3178742c-0c56-493c-a4e7-684b629cc659","added_by":"auto","created_at":"2026-03-06 18:26:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5499760,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/2fdd6a7c-fe96-4366-8ab2-373093e3b616.pdf"},{"id":94822475,"identity":"d16a0171-739f-41ea-b1b0-908dc03c8f89","added_by":"auto","created_at":"2025-10-31 06:24:35","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18100917,"visible":true,"origin":"","legend":"Supplementary Information","description":"","filename":"Supinfrastructurehazardassessment.docx","url":"https://assets-eu.researchsquare.com/files/rs-7055543/v1/8716e608f833da740106704d.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"High-Resolution Geomechanical Modeling Reveals Accelerating Infrastructure Risks from Permafrost Degradation in Northern Alaska","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe Arctic is on the front line of global climate change and is warming about four times faster than the global mean\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Climate warming increases mean annual ground temperature in the Arctic and drives permafrost degradation\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Permafrost is defined as ground that remains below 0℃ for at least two consecutive years\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Permafrost degradation leads to ground ice melting, talik formation\u0026mdash;defined as perennially unfrozen zones above or within the permafrost, thermokarst development, and associated thaw subsidence\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Degrading permafrost also alters the physical and mechanical properties of frozen soil and leads to reduced long-term strength\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e and lower bearing capacity\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Permafrost degradation has already caused irreversible damages to Arctic civil infrastructure and threatened Indigenous Arctic communities and the broader pan-Arctic economy\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Climate projections suggest that permafrost degradation will persist throughout the 21st century\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. In Alaska and the pan-Arctic region, civil infrastructure geohazards driven by permafrost degradation are expected to intensify, posing challenges to the future adaptation of social systems and the built environment\u003csup\u003e\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThaw settlement and bearing capacity reduction are two dominant geohazards threatening civil infrastructure in permafrost regions\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. When excess ground ice melts, thaw subsidence occurs due to the drainage of excess melt water. However, civil infrastructure imposes additional vertical stress on the ground; this leads to further settlement. Thaw settlement consists of volume reduction from both excess melt water drainage and stress-induced pore water drainage\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Although historically studied, current research primarily relies on \u0026ldquo;excess ice\u0026rdquo; models\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e to project thaw subsidence. The excess ice content is defined as the volumetric fraction of ice that exceeds the pore space of the thawed soil\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Consequently, the \u0026ldquo;excess ice\u0026rdquo; model underestimates thaw settlement for civil infrastructure, as it does not account for the consolidation of thawed soil due to pore water drainage. This underestimation may misinform regional planning and decision-making to support community adaptation efforts.\u003c/p\u003e\u003cp\u003eIn permafrost regions, bearing capacity of infrastructure foundation depends on the long-term strength of permafrost\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Long-term strength is defined as the maximum stress a soil can sustain without reaching a non-attenuating creep over the lifespan of an engineering structure\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. As temperature increases, long-term strength decreases, leading to bearing capacity reduction and potential infrastructure damage. Long-term strength also varies with ground ice content. Experimental results indicate that long-term strength may be significantly lower than short-term strength\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Therefore, applying long-term strength to quantify bearing capacity aligns with engineering design principles and provides a more realistic projection of infrastructure stability. However, current geospatial assessments have not used long-term strength to quantify the bearing capacity of foundations in permafrost.\u003c/p\u003e\u003cp\u003eTo date, civil infrastructure geohazard assessments in permafrost studies have primarily been conducted at a relatively coarse spatial resolution, e.g., pan-Arctic\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e and state scales\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Due to ongoing and rapid climate change in the Arctic, there is an urgent need to assess civil infrastructure geohazards at the community scale to aid in local infrastructure planning and design\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In addition, there is a need to integrate environmental variables with geomechanics-based engineering design parameters to project bearing capacity and thaw settlement in support of community-scale assessments. We address this knowledge gap by producing the first 21st century community-scale (30-m spatial resolution) geohazard projections for civil infrastructure built on permafrost. We focus on the Arctic Coastal Plain and four coastal communities in northern Alaska. Supplementary Fig.\u0026nbsp;1 depicts the extent of the Arctic Coastal Plain and the location of the four coastal communities. Continuous permafrost underlies the region, consisting mainly of ice-rich silty sand\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. See Section 1 of the Supplementary Information for a detailed description of the study region.\u003c/p\u003e\u003cp\u003eIn this study, we present an assessment framework that integrates geomechanical models with a process-based ground thermal model to evaluate the impact of permafrost degradation on civil infrastructure. Our model accounts for infrastructure loading effect on thaw settlement and calculates bearing capacity based on the creep failure mode of permafrost. This framework enables 30-m spatial resolution geohazard projections for civil infrastructure in the Arctic throughout the 21st century. We first quantify the magnitude and rate of changes in thaw settlement and bearing capacity at both regional (Arctic Coastal Plain) and local (four coastal communities) scales. We then assess the proportion of at-risk civil infrastructure in the Arctic Coastal Plain using the projected high-resolution geohazard data.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eComparison between modeled and observed thaw subsidence rates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe compare hindcast-modeled thaw subsidence rates (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\dot{S}}_{e}\\)\u003c/span\u003e\u003c/span\u003e) with published data from two regions with existing measurements: near Point Barrow and Prudhoe Bay (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In-situ measurements near Point Barrow indicate thaw subsidence rates ranging from 0.4 cm to 1.0 cm per year between 2003 and 2015, with a total subsidence of 8 cm to 15 cm by 2015\u003csup\u003e32\u003c/sup\u003e. In Prudhoe Bay, InSAR observations recorded thaw subsidence rates ranging from 0.1 cm to 0.4 cm per year from 1992 to 2000\u003csup\u003e33\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea illustrates the spatial patterns of simulated thaw subsidence (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{S}_{e}\\)\u003c/span\u003e\u003c/span\u003e) between 2003 and 2015 and between 1992 and 2000 using RCP8.5. The study regions are marked by red boxes. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb presents box plots of thaw subsidence in two-year intervals from 2005 to 2015 near Point Barrow. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec shows a yearly time series plot of thaw subsidence from 1992 to 2000 near Prudhoe Bay. In Point Barrow, the simulated thaw subsidence rate increases from 0.6 to 1.5 cm per year under RCP8.5 and remains constant at 0.3 cm per year under RCP4.5. The simulated thaw subsidence by 2015 ranges from 10 cm to 13 cm under RCP8.5. In Prudhoe Bay, the rate increases from 0.2 to 0.4 cm per year under RCP8.5 and remains constant at 0.1 cm per year under RCP4.5. The simulations indicate an accelerating trend in thaw subsidence rates under the RCP8.5 climate forcing scenario. Hindcast simulations under RCP8.5 closely align with in-situ measurements\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e and InSAR observations\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSpatiotemporal variability of thaw settlement across Arctic Coastal Plain by the 2090s\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBy the 2090s, higher projected thaw settlement is concentrated in the coastal regions from Wainwright to Point Lay and in lower-latitude areas under RCP8.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). This increased settlement is primarily driven by the higher compressibility of thawed soil, rapid thickening of the active layer and talik, and higher ground ice content in these regions. The mean thaw settlement (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{S}\\)\u003c/span\u003e\u003c/span\u003e) for the Arctic Coastal Plain reaches 1.1 m under RCP8.5 and 0.28 m under RCP4.5 when considering a vertical stress of 100 kPa due to infrastructure loading by the 2090s (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003eThe stress level of 100 kPa is selected to represent the typical additional load imposed by low-rise residential buildings in cold regions. In geotechnical engineering, such structures typically impose vertical stress increments ranging from 50 kPa to 150 kPa. The use of 100 kPa provides a conservative yet realistic estimate of infrastructure-induced settlement. Moreover, applying a consistent stress value across the Arctic Coastal Plain allows for a comparable assessment across the study area.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe scenario without vertical stress (\u003cem\u003eΔq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0 kPa) represents conditions where no civil infrastructure load is applied (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Under this scenario, our projections indicate that the mean thaw subsidence reaches 0.42 m under RCP8.5 and 0.13 m under RCP4.5 by the 2090s. To further assess the validity of our model, we compare our projections with existing vertical ground surface displacement measurements in the Arctic Coastal Plain. Recent studies report total subsidence of 12 cm from 2001 to 2018 in the Eastern Coastal Plain near Deadhorse, Alaska, and 12 cm from 2003 to 2018 in the Western Coastal Plain near Utqiaġvik, Alaska\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. These values correspond to a long-term subsidence rate of 0.07\u0026ndash;0.08 m per decade in the past two decades\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Based on the observed rates, total thaw subsidence across the Arctic Coastal Plain over the next seven decades (from the 2020s to the 2090s) can be projected to be 0.49\u0026ndash;0.56 m, which aligns with our projected mean thaw subsidence under RCP8.5.\u003c/p\u003e\u003cp\u003eWe statistically compare projected thaw settlement with and without infrastructure-induced vertical stress under RCP8.5 in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Both scenarios exhibit a right-skewed distribution. By the 2090s, the mean thaw subsidence without infrastructure-induced loading is approximately 60% lower than that under a vertical stress of 100 kPa. The cumulative distribution function curve for the \u003cem\u003eΔq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0 kPa scenario consistently shifts to the left. This shift indicates that infrastructure loading contributes to increased thaw settlement.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eOur projections underscore the importance of incorporating infrastructure loading into thaw settlement assessments. Increased vertical stress imposed by civil infrastructure leads to compression of thawed sediments and additional thaw strain. This compression-induced thaw strain accelerates ground deformation as the permafrost table declines over time. As the rate of permafrost table decline increases\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, the resulting additional deformation also increases over time. Neglecting these mechanical processes can significantly underestimate thaw settlement and potentially compromise infrastructure resilience planning in permafrost regions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSpatiotemporal variability of bearing capacity across Arctic Coastal Plain by the 2090s\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe project the spatial and temporal changes in ultimate bearing capacity (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{q}_{ult}\\)\u003c/span\u003e\u003c/span\u003e) using a semi-empirical equation derived from laboratory tests on ice-rich silty permafrost. The bearing capacity is calculated for a 5-m deep circular footing embedded in permafrost. This foundation represents a conventional pile foundation commonly used in northern Alaska\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. We assume creep failure as the governing mode of failure. Ice-rich permafrost typically has high short-term strength but gradually weakens over time under a constant loading, a phenomenon known as creep. As such, long-term creep failure is the primary mechanism of foundation failure in permafrost regions\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eBy the 2090s, nearly the entire Arctic Coastal Plain exhibits an ultimate bearing capacity below 200 kPa under RCP8.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). A significant portion of the region near Point Lay and low-latitude areas experience a complete loss of bearing capacity due to mean annual ground temperatures rising above 0℃. In these areas, we assume that thawed sediments with high water content cannot support infrastructure loads and result in a total loss of bearing capacity. Under RCP4.5, ultimate bearing capacity exhibits greater spatial variation by the 2090s. The coastline from Utqiaġvik to Peard Bay and from Camden Bay to Kaktovik generally maintains higher bearing capacity of around 2000 kPa. In contrast, the coastlines near Point Lay and low-latitude regions exhibit lower bearing capacity, falling below 600 kPa. Low bearing capacity is primarily attributed to the low volume fraction of soil particles and high ground temperatures. As a result, the soil shows low creep resistance and low long-term strength in these areas.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe mean ultimate bearing capacity (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e) of the Arctic Coastal Plain declines from 2050 kPa in the 2020s to 1470 kPa under RCP8.5 and 1588 kPa under RCP4.5 by the 2050s. By the 2090s, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e further decreases to 181 kPa under RCP8.5 and 1210 kPa under RCP4.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Compared to the 2020s, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e decreases by 29% under RCP8.5 and 22% under RCP4.5 by the 2050s. By the 2090s, the reduction reaches 91% under RCP8.5 and 41% under RCP4.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). Previous projections for the North Slope Borough indicate that the mean bearing capacity of a pile foundation ranges from 1500 to 2500 kPa by 2040\u003csup\u003e26\u003c/sup\u003e. Our projections align with this range under both RCP8.5 and RCP4.5 by the 2040s. However, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e declines more rapidly over time under RCP8.5. Our projections indicate a severe long-term reduction in bearing capacity and potentially catastrophic damage to civil infrastructure in the absence of adequate design and mitigation measures.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAccelerating thaw settlement in four coastal communities of northern Alaska\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThaw settlement accelerates at both regional (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and local (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) scales. Utqiaġvik shows the lowest thaw settlement rate among the four communities, with mean thaw settlement reaching 0.13 m by the 2050s and 0.5 m by the 2090s (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). In Wainwright, projected thaw settlement increases from 0.15 m in the 2050s to 1.1 m by the 2090s (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Point Lay exhibits the highest rate of thaw settlement, reaching 0.19 m by the 2050s and 2.7 m by the 2090s (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). In Kaktovik, thaw settlement is projected to reach 0.3 m by the 2050s and 1.0 m by the 2090s (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed).\u003c/p\u003e\u003cp\u003eThe variation in projected thaw settlement among the four coastal communities is primarily driven by differences in the compressibility of thawed soil and the rate of permafrost table decline. In Utqiaġvik, permafrost typically exhibits a lower compressibility index and a slower decline in the permafrost table over time. In contrast, Point Lay experiences a rapid deepening of the permafrost table and a higher compressibility index (Supplementary Figs.\u0026nbsp;2 and 3), which leads to a thicker thawed layer for consolidation and a more pronounced volume decrease under vertical loading.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBy the 2030s, projected thaw settlement remains low across most areas of the four coastal communities and generally below 0.1 m compared to the 2020s (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). However, localized zones of higher settlement\u0026mdash;ranging from 0.7 m to 0.8 m\u0026mdash;are observed along the Point Lay coastline and near the Kokolik River delta. By the 2050s, thaw settlement exhibits greater spatial heterogeneity. The coastlines of Utqiaġvik and Wainwright show increasing thaw settlement. In Point Lay, settlement intensifies along both the coastline and the Kokolik River delta. In Kaktovik, high settlement areas emerge in the northwestern and southeastern coastal regions of Barter Island.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis increased thaw settlement by mid-century is primarily driven by the rapid thickening of the active layer near the coastlines and near the river deltas. By the 2090s, widespread talik development is projected across all four coastal communities. Talik development contributes significantly to thaw settlement. Extensive talik formation is expected in the northeastern part of Utqiaġvik, where thermokarst lakes are present. Talik also develops extensively in northeastern Wainwright, along the Kokolik River delta in Point Lay, and in the northwestern and southeastern coastal areas of Barter Island near Kaktovik. Talik formation in these regions is attributed to the heat storage effect of surface water\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e and the presence of saline ground material\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eNonlinear bearing capacity loss in four coastal communities of northern Alaska\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe bearing capacity decreases nonlinearly over time at both regional (see Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) and local (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) scales. In Utqiaġvik, the rate of decrease in mean bearing capacity remains relatively low in the first half of the century. By the 2050s, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e declines from 1750 kPa to 1370 kPa, representing a 22% reduction (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). However, the rate of decline accelerates over time. By the 2090s, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e is projected to reach 157 kPa with a 91% reduction compared to the 2020s. In Wainwright and Point Lay, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e declines more rapidly in the first half of the century and reaches critically low values by the 2090s. Specifically, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e in Wainwright decreases from 1780 kPa to 1140 kPa by the 2050s \u0026mdash;a 36% reduction. By the 2090s, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e further declines by 95% compared to the 2020s (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). Among the four communities, Point Lay exhibits the most severe decline in \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e decreases from 1860 kPa to 600 kPa (68% reduction) by the 2050s and ultimately reaches 0 kPa by the 2090s (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec). Kaktovik experiences a relatively less severe decline in \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed). The projected \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{q}}_{ult}\\)\u003c/span\u003e\u003c/span\u003e decreases from 2810 kPa in the 2020s to 2190 kPa by the 2050s (22% reduction) and 320 kPa by the 2090s (89% reduction).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eChanges in mean annual ground temperature are the primary factor influencing the evolution of ultimate bearing capacity over time across the four coastal communities. Permafrost near Utqiaġvik generally exhibits lower ground temperatures and a slower rate of increase under the RCP8.5 climate forcing. In contrast, the coastline spanning from Point Lay to Wainwright experiences higher ground temperatures and a more rapid increase over time. Elevated temperatures reduce the creep resistance of permafrost, leading to lower long-term strength and ultimately a significant decline in bearing capacity.\u003c/p\u003e\u003cp\u003eThe projected ultimate bearing capacity exhibits high spatial heterogeneity across the four coastal communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). In Utqiaġvik, higher bearing capacity is concentrated near the coastline. A similar spatial pattern is observed in Wainwright, where bearing capacity remains higher near the coastline and lower in inland areas by the 2050s. Point Lay exhibits relatively low bearing capacity across the entire community in both the 2030s and the 2050s compared with the other three communities. In Kaktovik, lower bearing capacity is concentrated in the northwestern and southeastern regions of Barter Island by the 2050s. By the 2090s, bearing capacity across the four communities decreases to low levels showing reduced spatial variability.\u003c/p\u003e\u003cp\u003eAt a given time, the spatial distribution of bearing capacity is primarily governed by variations in the volumetric fraction of soil particles (\u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e). A higher \u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e is directly related to a higher bulk density for the same soil type. Experimental tests suggest that denser, ice-rich silty permafrost exhibits higher creep resistance and long-term strength due to the densification effect on deformation\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Consequently, when other soil conditions remain unchanged, a higher \u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e tends to result in higher bearing capacity. In Utqiaġvik and Wainwright, regions with higher \u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e\u0026mdash;primarily near the coastline\u0026mdash;exhibit correspondingly higher bearing capacity. Similarly, higher bearing capacity is concentrated in the northeastern region of Barter Island in Kaktovik due to the relatively high \u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e. Although \u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e in Point Lay is also relatively high, ranging from 0.35 to 0.45, a large portion of the region experiences a rapid rise in mean annual ground temperatures above 0\u0026deg;C by the 2090s. As a result, Point Lay undergoes a drastic loss of bearing capacity due to permafrost degradation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e21st century infrastructure risks under permafrost degradation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe quantify 21st century infrastructure risks (\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003erisk\u003c/em\u003e\u003c/sub\u003e) on the Alaska Arctic Coastal Plain. See Methods for a detailed description of infrastructure risk assessment. Infrastructure risk remains low by the 2050s (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Our projections indicate that the percentage of buildings at risk is 7%, 4%, and 0% for design safety factors of 1.6, 2.0, and 3.0, respectively, under RCP8.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea). By the 2050s, 2%-3% of roads and 1%-3% of pipelines are also at risk. However, infrastructure risk significantly increases after a tipping point in the 2060s. By the 2070s, 68% of buildings are projected to experience at least a 50% reduction in bearing capacity. Forty-five percent of roads and 52% of pipelines are projected to exceed the 0.2 m settlement threshold under moderate stress conditions. By the 2090s, our projections indicate that 80%-83% of buildings are at risk due to substantial bearing capacity reduction. 58%-60% of roads and 87%-90% of pipelines are projected to be exposed to high thaw settlement. Under RCP4.5, infrastructure risks are significantly lower (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eb). By the 2090s, projections indicate that 6%-36% of buildings and 2%-3% of roads and pipelines are at risk under RCP4.5. Shaded areas in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e represent uncertainties associated with variations in factors of safety and vertical stress.\u003c/p\u003e\u003cp\u003eThe tipping point around the 2060s results from the long-term effects of climate change on permafrost. By the 2060s, large areas exhibit increased thaw settlement and a decline in bearing capacity beyond critical thresholds. Geohazards exceeding these thresholds place most infrastructure on the Arctic Coastal Plain at high risk and mark the tipping point. Our projections underscore the urgency of adaptation-based policies and mitigation measures, along with the need to reduce global emissions to prevent unprecedented infrastructure damage. However, our projections do not account for uncertainties related to future human activities. The impact of human activities could either exacerbate infrastructure risks in the absence of adaptation strategies or mitigate them through proactive planning and engineering solutions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo enable early warning systems and anticipatory actions for mitigating Arctic infrastructure risks, state and local governments and Indigenous communities require accurate and high-spatial-resolution tools and projections to visualize infrastructure geohazards. Projecting the spatiotemporal rate and magnitude of these geohazards is essential to support future adaptation efforts and ensure the resilience of both social systems and the built environment to the unprecedented environmental changes in the Arctic. This study presents a framework capable of generating high-resolution, time-series hazard maps through the end of the 21st century. The outcomes of this study can assist planners and policymakers in identifying high-risk areas, implementing mitigation measures, and strategically planning future infrastructure at the community scale.\u003c/p\u003e\u003cp\u003eWhen compared with existing literature, our work presents several key innovations that distinguish this study from earlier hazard assessments. First, our framework is geomechanics-based, in contrast to previous studies that primarily relied on indices or statistical models alone. By integrating geomechanical models with a process-based ground thermal model, the approach captures the mechanical behavior of permafrost under varying stress and thermal conditions more accurately. Second, our thaw settlement projections account for settlement induced by increased vertical stress. The model therefore considers how additional loads from civil infrastructure contribute to increased surface deformation. This infrastructure loading effect is often overlooked in previous studies, where thaw settlement is typically estimated based solely on excess melt water drainage. Third, many prior hazard mapping approaches focused on short-term permafrost stability, without adequately accounting for its progressive weakening. However, permafrost used as a foundation material often experiences creep failure when accumulated strain exceeds the failure strain within a structure’s service life. We address this gap by estimating bearing capacity based on the long-term strength of ice-rich permafrost. Long-term strength is a critical factor in cold region foundation design and is related to creep resistance of the frozen soil. Finally, our framework presents high-resolution 30-m hazard maps, substantially finer than the coarser-scale outputs (e.g., 1 km or 10 km grids) in previous studies. The high spatial resolution is essential for identifying localized risks related to infrastructure damage, socio-economic impact, and landscape evolution. With these four innovations, our study provides the first precise, geomechanics-based framework for understanding how permafrost degradation and associated hazards evolve at both local and regional scales.\u003c/p\u003e\u003cp\u003eDespite the strengths of our approach, the infrastructure hazard assessment is subject to uncertainties related to data, process representation, human influences, climate forcing, and model validation (see Section 4 of the Supplementary Information). First, the modeling of permafrost dynamics is constrained by limited field-based ground measurements. Second, the time-dependent consolidation behavior of thawing soils and the time required to reach ultimate settlement\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e are not considered in the current framework. Third, real-world engineering practices include a wide range of foundation types and dimensions. Finally, in terms of subsurface features, the current framework does not model the development of cryopegs\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e or account for the role of cryopegs in permafrost stability. Future research is recommended to reduce uncertainty and further improve hazard mapping by addressing limitations of the current framework.\u003c/p\u003e\u003cp\u003eIn conclusion, our findings reveal that thaw settlement is accelerating and bearing capacity is decreasing nonlinearly at both regional (Arctic Coastal Plain) and local (Utqiaġvik, Wainwright, Point Lay, and Kaktovik) scales. In the four coastal communities, thaw settlement is projected to reach 0.15–0.3 m by the 2050s and 0.5–2.7 m by the 2090s under RCP8.5. Omitting the effect of infrastructure-induced stress leads to an underestimation of thaw settlement. Rising ground temperatures weaken permafrost, resulting in a 22–68% reduction in bearing capacity by the 2050s and 88–100% by the 2090s in the four coastal communities. Permafrost degradation places 80% of buildings, 60% of roads, and 90% of pipelines at high risk by the 2090s across the Arctic Coastal Plain. While the projected percentage of infrastructure at high risk remains below 10% by the mid-century, a clear tipping point of infrastructure failure emerges in the 2060s. Beyond the tipping point, most infrastructure will face high risk if mitigation measures are not implemented and greenhouse gas emissions continue unabated. Our findings underscore the urgent need for proactive adaptation strategies to support coastal communities. Moving forward, further research focused on high-resolution hazard mapping at the community scale will be critical. Future efforts should also integrate Indigenous knowledge to co-produce evidence-based decision-making frameworks for Arctic and sub-Arctic regions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eData\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe obtained soil information (i.e., soil bulk density, clay content) from SoilGrids\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. SoilGrids provids a global estimation of soil properties at a spatial resolution of 250 m. All geospatial data are resampled to 30 m in our analysis to match the outputs from the process-based ground thermal model. The estimated soil properties were provided for seven standard depths from the ground surface to 200 cm. The soil properties were derived using machine learning algorithms trained on global soil profiles. We used the depth-weighted average to obtain soil properties at each location. The soil bulk density and clay content are shown in Supplementary Figs.\u0026nbsp;2a and 2b.\u003c/p\u003e\u003cp\u003eWe used the ground ice map of northern Alaska\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e in our assessment. The ground ice map illustrates the distribution of excess ground ice volume within the upper five meters of permafrost. Supplementary Fig.\u0026nbsp;2c shows the ground ice distribution across the Arctic Coastal Plain.\u003c/p\u003e\u003cp\u003eThe permafrost temperature dynamics were simulated using the GIPL-2.0 model\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. GIPL-2.0 is a process-based model that solves the 1-D nonlinear heat conduction equation with phase change to simulate permafrost conditions, including ground temperature, active layer thickness, and talik thickness. The governing equation is presented in Eq.\u0026nbsp;(1)\u003csup\u003e44\u003c/sup\u003e.\u003c/p\u003e\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\left({C}_{v}+L\\frac{\\partial\\:{\\theta\\:}_{w}\\left(T,z\\right)}{\\partial\\:T}\\right)\\frac{\\partial\\:T}{\\partial\\:t}=\\frac{\\partial\\:}{\\partial\\:z}\\left(\\lambda\\:\\frac{\\partial\\:T\\left(z,t\\right)}{\\partial\\:z}\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003cp\u003ewhere \u003cem\u003ez\u003c/em\u003e is the depth from the soil or snow surface, \u003cem\u003eT\u003c/em\u003e is the ground temperature, \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003ev\u003c/em\u003e\u003c/sub\u003e represents the volumetric heat capacity, \u003cem\u003eλ\u003c/em\u003e is the thermal conductivity, \u003cem\u003eL\u003c/em\u003e is the volumetric latent heat of fusion, and \u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003ew\u003c/em\u003e\u003c/sub\u003e represents the volumetric water content.\u003c/p\u003e\u003cp\u003eThe simulations utilized downscaled air-temperature datasets\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e to drive permafrost dynamics at a 30-m spatial resolution under the RCP4.5 and RCP8.5 climate forcing. Ground thermal properties and volumetric water content were parameterized and upscaled based on high-resolution ecosystem type classifications and borehole data. Supplementary Figs.\u0026nbsp;2d, 2e, and 2f illustrate the projected permafrost conditions by the 2050s. Suppelmentary Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eh, and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ei depict the permafrost projections in the 2090s. We incorporate the existing simulation data into our geohazard assessment to evaluate the impacts of permafrost degradation on civil infrastructure.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssessment of Thaw Settlement\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWhen permafrost warms and thaws, excess melt water first drains out without the compression of the soil skeleton\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Thaw subsidence related to excess ice melt can be expressed as\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e:\u003c/p\u003e\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:{S}_{e}={\\varDelta\\:Z}_{ALT+TT}{\\theta\\:}_{excess,\\:\\:ice}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003cp\u003ewhere \u003cem\u003eS\u003c/em\u003e\u003csub\u003e\u003cem\u003ee\u003c/em\u003e\u003c/sub\u003e is the subsidence related to excess ice melt, \u003cem\u003eΔZ\u003c/em\u003e represents changes in the permafrost table due to active layer thickening or talik development, \u003cem\u003eALT\u003c/em\u003e denotes active layer thickness, \u003cem\u003eTT\u003c/em\u003e is talik thickness, and \u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003eexcess,ice\u003c/em\u003e\u003c/sub\u003e is the volumetric content of excess ice. Supplementary Table\u0026nbsp;1 contains the notations of parameters used in the geomechanical modeling.\u003c/p\u003e\u003cp\u003eCalculating thaw subsidence solely from excess ice content is valid only when the compression of the soil skeleton is negligible. However, vertical stress increases from infrastructure loading cause additional volume reduction due to pore water drainage in the thawed sediment. For ice-rich permafrost, whether coarse-grained or fine-grained, the volume decrease during thawing consists of three main components: phase change, drainage of excess melt water, and compression of thawed sediments under the applied stress\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. After the excess melt water drains out, the void ratio of the thawed soil follows a semilogarithmic linear relationship with the stress carried by the soil skeleton\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. Therefore, the volume change in thawed permafrost due to pore water drainage can be expressed as follows:\u003c/p\u003e\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:{S}_{c}=\\frac{{e}_{th}-e}{1+{e}_{th}}\\varDelta\\:{Z}_{ALT+TT}=\\frac{\\varDelta\\:{Z}_{ALT+TT}}{1+{e}_{th}}{C}_{c}^{*}\\text{log}\\frac{{\\sigma\\:}_{0}^{{\\prime\\:}}+\\varDelta\\:q}{{\\sigma\\:}_{0}^{{\\prime\\:}}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003cp\u003ewhere \u003cem\u003eS\u003c/em\u003e\u003csub\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sub\u003e is the settlement related to compression of the soil skeleton, \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003eth\u003c/em\u003e\u003c/sub\u003e represents the thawed void ratio after excess melt water drains out, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{c}^{*}\\)\u003c/span\u003e\u003c/span\u003e is the coefficient of compressibility of the thawed soil (i.e., the slope of the semilogarithmic linear curve between void ratio and stress carried by soil skeleton), \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{0}^{{\\prime\\:}}\\)\u003c/span\u003e\u003c/span\u003e is the residual stress, which is defined as the initial effective stress within the soil skeleton when the soil thaws under undrained conditions\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003eΔq\u003c/em\u003e is the vertical stress increment caused by infrastructure loading, and \u003cem\u003ee\u003c/em\u003e is the thawed void ratio at\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{0}^{{\\prime\\:}}\\)\u003c/span\u003e\u003c/span\u003e + \u003cem\u003eΔq\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThe settlement induced by phase change from frozen state to thawed state is expressed as:\u003c/p\u003e\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:{S}_{p}=\\frac{{e}_{f}-{e}_{i}^{*}}{1+{e}_{f}}{\\varDelta\\:Z}_{ALT+TT}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003cp\u003ewhere \u003cem\u003eS\u003c/em\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e is the settlement related to phase change, \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e is the frozen void ratio, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{e}_{i}^{*}\\)\u003c/span\u003e\u003c/span\u003e is the initial thawed void ratio.\u003c/p\u003e\u003cp\u003eWe use bulk density and specific gravity (based on soil types) to calculate \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e for saturated permafrost in the Arctic Coastal Plain. Since the void ratio decreases from \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e to \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{e}_{i}^{*}\\)\u003c/span\u003e\u003c/span\u003e solely due to phase change, the relationship between \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{e}_{i}^{*}\\)\u003c/span\u003e\u003c/span\u003e is expressed as:\u003c/p\u003e\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$$\\:{e}_{i}^{*}=\\frac{{e}_{f}}{1.09}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003cp\u003eThe total thaw settlement \u003cem\u003eS\u003c/em\u003e is therefore written as:\u003c/p\u003e\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$$\\:S={S}_{p}+{S}_{e}+{S}_{c}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e\u003cp\u003eWe use experimentally determined relationships to calculate \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{c}^{*}\\)\u003c/span\u003e\u003c/span\u003e and \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003eth\u003c/em\u003e\u003c/sub\u003e. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{0}^{{\\prime\\:}}\\)\u003c/span\u003e\u003c/span\u003e is assumed to be 0.1 kPa for ice-rich permafrost\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. The expression for \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{c}^{*}\\)\u003c/span\u003e\u003c/span\u003e is adopted from an empirical equation developed using 108 tests on ice-rich permafrost\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e:\u003c/p\u003e\u003cdiv id=\"Equ7\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ7\" name=\"EquationSource\"\u003e\n$$\\:{C}_{c}^{*}=\\left(0.0051clay\\%-0.18\\right)\\text{log}{e}_{i}^{*}+(0.0015clay\\%+0.096)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e7\u003c/div\u003e\u003c/div\u003e\u003cp\u003ewhere \u003cem\u003eclay%\u003c/em\u003e represents gravimetric clay content.\u003c/p\u003e\u003cp\u003eWe calculate \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003eth\u003c/em\u003e\u003c/sub\u003e based on empirical relationships between \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003eth\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e developed from thaw settlement tests ice-rich permafrost\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e:\u003c/p\u003e\u003cdiv id=\"Equ8\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ8\" name=\"EquationSource\"\u003e\n$$\\:{e}_{th}=1.82\\text{log}{e}_{f}+0.95$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e8\u003c/div\u003e\u003c/div\u003e\u003cp\u003eSupplementary Figs.\u0026nbsp;3a, 3c, and 3e show the spatial distribution of \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003eth\u003c/em\u003e\u003c/sub\u003e, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{c}^{*}\\)\u003c/span\u003e\u003c/span\u003e, respectively. Higher values of \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003eth\u003c/em\u003e\u003c/sub\u003e are concentrated in the higher-latitude tundra. However, permafrost along the coastline from Utqiaġvik to Wainwright exhibits lower values of \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003eth\u003c/em\u003e\u003c/sub\u003e. A similar pattern is observed for \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{c}^{*}\\)\u003c/span\u003e\u003c/span\u003e, with lower values prevalent near the coastline from Utqiaġvik to Wainwright and around Elson Lagoon along the Beaufort Sea. Supplementary Figs.\u0026nbsp;3b, 3d, and 3f present the histograms of \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003eth\u003c/em\u003e\u003c/sub\u003e, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{c}^{*}\\)\u003c/span\u003e\u003c/span\u003e, respectively. Each parameter follows a normal distribution. The mean and median values are 2.15 and 2.08 for \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e, 1.54 and 1.53 for \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003eth\u003c/em\u003e\u003c/sub\u003e, and 0.24 and 0.25 for \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{c}^{*}\\)\u003c/span\u003e\u003c/span\u003e. These values fall within typical ranges observed for ice-rich permafrost.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssessment of Bearing Capacity\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe long-term strength (\u003cem\u003eσ\u003c/em\u003e\u003csub\u003e\u003cem\u003elt\u003c/em\u003e\u003c/sub\u003e) for ice-rich permafrost is calculated using Eq.\u0026nbsp;(9)\u003csup\u003e22\u003c/sup\u003e.\u003c/p\u003e\u003cdiv id=\"Equ9\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ9\" name=\"EquationSource\"\u003e\n$$\\:{\\sigma\\:}_{lt}={\\left(\\frac{{ϵ}_{f}}{{t}_{f}A}\\right)}^{1/n}\\:$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e9\u003c/div\u003e\u003c/div\u003e\u003cp\u003ewhere \u003cem\u003eε\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e is the failure strain. For ice-rich permafrost, \u003cem\u003eε\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e is assumed to be 0.1\u003csup\u003e22\u003c/sup\u003e. \u003cem\u003et\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e represents the service life of civil infrastructure. We set \u003cem\u003et\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e to 50 years. \u003cem\u003eA\u003c/em\u003e and \u003cem\u003en\u003c/em\u003e are creep parameters in Glen’s flow law\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. We use semi-empirical equations to determine \u003cem\u003eA\u003c/em\u003e and \u003cem\u003en\u003c/em\u003e based on volumetric soil particle fraction (\u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e) and ground temperature (\u003cem\u003eT\u003c/em\u003e) at 5-m depth, which represents the depth of conventional pile foundations. For saturated permafrost, \u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e is derived from bulk density and specific gravity. The semi-empirical equations were developed through unconfined creep tests of 29 ice-rich silty permafrost samples from northern Alaska\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Eq.\u0026nbsp;(\u003cspan refid=\"Equ10\" class=\"InternalRef\"\u003e10\u003c/span\u003e) presents the expression for the creep parameters:\u003c/p\u003e\u003cdiv id=\"Equ10\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ10\" name=\"EquationSource\"\u003e\n$$\\:A=\\text{exp}\\left(-14.1-154.1{\\theta\\:}_{s}+\\frac{186.9}{1+\\left|T\\right|}{\\theta\\:}_{s}\\right)\\:n=1.4+20.1{\\theta\\:}_{s}-\\frac{19.6}{1+\\left|T\\right|}{\\theta\\:}_{s}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e10\u003c/div\u003e\u003c/div\u003e\u003cp\u003eSupplementary Fig.\u0026nbsp;4 illustrates the projected creep parameters and long-term strength of permafrost for the 2020s, 2050s, and 2090s under RCP8.5 climate forcing. By the 2090s, the mean annual ground temperature exceeds 0℃ in some areas, leading to permafrost loss and complete bearing capacity reduction. Grid cells where the mean annual ground temperature exceeds 0℃ are excluded from the analysis. In the 2020s, \u003cem\u003eσ\u003c/em\u003e\u003csub\u003e\u003cem\u003elt\u003c/em\u003e\u003c/sub\u003e is relatively lower in higher-latitude coastal regions due to lower soil particle fractions. In contrast, permafrost along the coastline from Utqiaġvik to Wainwright exhibits higher \u003cem\u003eσ\u003c/em\u003e\u003csub\u003e\u003cem\u003elt\u003c/em\u003e\u003c/sub\u003e values. However, as ground temperatures rise rapidly in lower-latitude regions by the 2050s and 2090s, spatial variations in \u003cem\u003eσ\u003c/em\u003e\u003csub\u003e\u003cem\u003elt\u003c/em\u003e\u003c/sub\u003e become less pronounced.\u003c/p\u003e\u003cp\u003eSupplementary Fig.\u0026nbsp;5 presents the histograms of creep parameters and long-term strength for the 2020s, 2050s, and 2090s under RCP8.5. Each parameter follows a normal distribution. An exception is observed in the 2090s, where \u003cem\u003eσ\u003c/em\u003e\u003csub\u003e\u003cem\u003elt\u003c/em\u003e\u003c/sub\u003e exhibits a right-skewed distribution. The mean and median values of \u003cem\u003elogA\u003c/em\u003e increase from − 24.0 in the 2020s to -8.4 and − 8.5 in the 2090s, respectively. The mean and median values for \u003cem\u003en\u003c/em\u003e decrease from 7.0 in the 2020s to 3.2 and 3.1 in the 2090s. These values are consistent with previously documented creep parameters for ice-rich permafrost\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. The mean \u003cem\u003eσ\u003c/em\u003e\u003csub\u003e\u003cem\u003elt\u003c/em\u003e\u003c/sub\u003e declines sharply from 305.6 kPa in the 2020s to 11.5 kPa in the 2090s. This sharp decrease indicates a substantial loss of permafrost strength due to climate change.\u003c/p\u003e\u003cp\u003eThe ultimate bearing capacity (\u003cem\u003eq\u003c/em\u003e\u003csub\u003e\u003cem\u003eult\u003c/em\u003e\u003c/sub\u003e) is determined using \u003cem\u003eσ\u003c/em\u003e\u003csub\u003e\u003cem\u003elt\u003c/em\u003e\u003c/sub\u003e based on Eq.\u0026nbsp;(11)\u003csup\u003e55\u003c/sup\u003e:\u003c/p\u003e\u003cdiv id=\"Equ11\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ11\" name=\"EquationSource\"\u003e\n$$\\:{q}_{ult}={p}_{0}{N}_{q}+c{N}_{c}\\:$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e11\u003c/div\u003e\u003c/div\u003e\u003cp\u003ewhere \u003cem\u003eρ\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e is the ground overburden pressure at the foundation level. We calculate \u003cem\u003eρ\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e using specific gravity and foundation depth. \u003cem\u003ec\u003c/em\u003e represents temperature-dependent cohesion, while \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003eq\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sub\u003e are the bearing capacity factors.\u003c/p\u003e\u003cp\u003eFor ice-rich permafrost with friction angle (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varphi\\:\\)\u003c/span\u003e\u003c/span\u003e) of zero, \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003eq\u003c/em\u003e\u003c/sub\u003e is equal to 1 and \u003cem\u003ec\u003c/em\u003e is equal to half of \u003cem\u003eσ\u003c/em\u003e\u003csub\u003e\u003cem\u003elt\u003c/em\u003e\u003c/sub\u003e. \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sub\u003e for a circular footing is defined by Eq.\u0026nbsp;(12)\u003csup\u003e55\u003c/sup\u003e.\u003c/p\u003e\u003cdiv id=\"Equ12\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ12\" name=\"EquationSource\"\u003e\n$$\\:{N}_{c}=1+\\frac{4}{3}\\left(n+\\text{ln}\\frac{2}{3{\\epsilon\\:}_{f}}\\right)\\:$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e12\u003c/div\u003e\u003c/div\u003e\u003cp\u003eFor a strip footing, \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sub\u003e is defined by Eq.\u0026nbsp;(13)\u003csup\u003e56\u003c/sup\u003e.\u003c/p\u003e\u003cdiv id=\"Equ13\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ13\" name=\"EquationSource\"\u003e\n$$\\:{N}_{c}=\\frac{2}{\\sqrt{3}}\\left[1+n-\\text{ln}{\\epsilon\\:}_{f}\\sqrt{3}\\right]$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e13\u003c/div\u003e\u003c/div\u003e\u003cp\u003e\u003cb\u003eAssessment of Infrastructure Risks\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe high spatial resolution (30-m), geomechanics-based projections enable a community-scale assessment of geohazards caused by permafrost degradation. Raster cell values within each community polygon are extracted and analyzed using time-series plots to assess the rate and magnitude of thaw settlement (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) and ultimate bearing capacity changes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) in each community.\u003c/p\u003e\u003cp\u003eWe assess infrastructure risks based on projected thaw settlement and bearing capacity reduction. Infrastructure data are obtained from the North Slope Science Initiative. Supplementary Fig.\u0026nbsp;6 outlines the workflow in ArcGIS Pro\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. The analysis begins by extracting raster maps of bearing capacity and thaw settlement based on predefined threshold values. The threshold values are denoted as \u003cem\u003eθ\u003c/em\u003e\u003csub\u003e\u003cem\u003ebc\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e*\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eS\u003c/em\u003e\u003csup\u003e\u003cem\u003e*\u003c/em\u003e\u003c/sup\u003e for bearing capacity reduction and thaw settlement, respectively. The extracted hazard maps are then converted into polygon features and intersected with infrastructure locations to identify at-risk infrastructure. Next, we calculate the area or length of at-risk infrastructure. The fraction of at-risk infrastructure is calculated as the ratio of at-risk area or length to the total infrastructure extent.\u003c/p\u003e\u003cp\u003eTo represent road-induced loading conditions, we select vertical stress values of 10, 30, and 50 kPa. These stress values capture the range from conservative far-field stress to localized peak stress typically observed under roadways. For pipelines, vertical stress values of 5, 15, and 25 kPa are used to reflect common pipeline-induced loading conditions. For buildings, infrastructure at high risk is determined based on the loss of bearing capacity exceeding a threshold value (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\theta\\:}_{bc}^{*}\\)\u003c/span\u003e\u003c/span\u003e) of 35%, 50%, and 65%. The selected \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\theta\\:}_{bc}^{*}\\)\u003c/span\u003e\u003c/span\u003e values correspond to design safety factors of 1.6, 2.0, and 3.0, respectively, assuming infrastructure damage occurs when the bearing capacity falls below a safety factor of 1. Design safety factors are the factors used in foundation designs; a higher factor represents a more conservative design applied in construction.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e\u003cp\u003eZ.W. and M.X. designed the study. D.N. developed the permafrost ground thermal model. Z.W. developed the geomechanics-based method, performed the analysis and wrote the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThis work was supported by the U.S. National Science Foundation (NSF) Award RISE-1927718.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRantanen M et al (2022) The Arctic has warmed nearly four times faster than the globe since 1979. 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ArcGIS Pro (Version 3.X) [Computer software] (2024) ; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.esri.com/en-us/arcgis/products/arcgis-pro/overview\u003c/span\u003e\u003cspan address=\"https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e "}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7055543/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7055543/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePermafrost degradation causes irreversible damage to Arctic civil infrastructure and threatens the broader pan-Arctic economy. Currently, the lack of community-scale, geomechanics-based mapping of Arctic infrastructure hazards hinders effective local infrastructure planning. Here, we develop a novel framework that integrates physics-constrained geotechnical models with a process-based ground thermal model to assess the 21st century changes in thaw settlement and bearing capacity of civil infrastructure foundations at a 30-m spatial resolution. We find that settlement is accelerating and bearing capacity is decreasing nonlinearly at both regional and local scales. By mid-century, less than 10% of the infrastructure in northern Alaska is projected to be at high risk; however, a tipping point emerges around the 2060s. Beyond the tipping point, most infrastructure will face high risk if mitigation measures are not implemented. Our results underscore the urgent need for proactive adaptation strategies to protect Arctic infrastructure from permafrost degradation-induced hazards.\u003c/p\u003e","manuscriptTitle":"High-Resolution Geomechanical Modeling Reveals Accelerating Infrastructure Risks from Permafrost Degradation in Northern Alaska","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-31 06:24:30","doi":"10.21203/rs.3.rs-7055543/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-earth-and-environment","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsenv","sideBox":"Learn more about [Communications Earth and Environment](https://www.nature.com/commsenv/)","snPcode":"","submissionUrl":"","title":"Communications Earth \u0026 Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"124faa57-6784-4c3a-affb-3a6455b3f582","owner":[],"postedDate":"October 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":51230329,"name":"Earth and environmental sciences/Environmental social sciences/Climate-change adaptation"},{"id":51230330,"name":"Physical sciences/Engineering/Civil engineering"},{"id":51230331,"name":"Earth and environmental sciences/Climate sciences/Cryospheric science"},{"id":51230332,"name":"Earth and environmental sciences/Environmental social sciences/Climate-change impacts/Governance"},{"id":51230333,"name":"Earth and environmental sciences/Natural hazards"}],"tags":[],"updatedAt":"2026-03-06T18:26:17+00:00","versionOfRecord":{"articleIdentity":"rs-7055543","link":"https://doi.org/10.1038/s43247-026-03240-5","journal":{"identity":"communications-earth-and-environment","isVorOnly":false,"title":"Communications Earth \u0026 Environment"},"publishedOn":"2026-01-24 00:00:00","publishedOnDateReadable":"January 24th, 2026"},"versionCreatedAt":"2025-10-31 06:24:30","video":"","vorDoi":"10.1038/s43247-026-03240-5","vorDoiUrl":"https://doi.org/10.1038/s43247-026-03240-5","workflowStages":[]},"version":"v1","identity":"rs-7055543","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7055543","identity":"rs-7055543","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}